annual progress report i. overview -...

Legumes Project Grant No 10-473

ANNUAL PROGRESS REPORT

I. Overview This is a participatory, systems-oriented collaborative research project aimed at improving the livelihoods of smallholder farmers in Western Kenya through the use of promising multipurpose grain legumes. The project is led by The Kenya Agricultural Research Institute (KARI-Kakamega). KARI is collaborating with six other institutions in implementing the project. These are: i) Cornell University (USA), ii) University of Nairobi (Kenya), iii) Egerton University (Kenya), iv) ARDAP (an NGO in Western Kenya), v) REFSO (an NGO in Western Kenya), and AVENE CBO (a community-based organization in Western Kenya). High population pressure on land has led to farm fragmentation in Western Kenya resulting in continuous cropping by farmers in an attempt to ensure household food security. Continuous cropping by smallholders without inputs of fertilizers to replenish soil nutrients has resulted in soil fertility degradation and a decline in productivity. Mineral fertilizers are too costly for smallholder farmers and amounts used are insufficient to generate levels of productivity required to attain food security. The smallholder production systems in Western Kenya are inherently complex and composed of multiple components that are interrelated and interact with each other. In an effort to ensure household food security, farmers pursue different production objectives and livelihood strategies. The project is working with groups of smallholder farmers in several sites in Western Kenya to develop, refine and scale-out promising options for improving the productivity of the systems. The project’s strategy is to use multipurpose grain legumes as an entry point and employ a systems approach (See the project theory of change depicted by Figure 1 below). Several promising multipurpose grain legumes have been identified that have the potential for re-invigorating the smallholder farming systems, improving system productivity, household food security and income. The potential benefits include improving soil fertility through inputs of fixed atmospheric nitrogen, provision of high protein content food for humans, high quality fodder for livestock, and increased opportunities for household income generation. To do this within a systems perspective, the project has brought together collaborators from different disciplines, including soil science, plant pathology, entomology, agricultural economics, and agricultural extension. The outcome expected is increased agro-ecological intensification and sustainable improvements in productivity, food security, increased incomes and a reduction in poverty in target Western Kenya smallholder systems. The collaborative and systems-oriented participatory research being implemented by the project will significantly contribute to institutional capacity building, particularly the capacity to implement systems-oriented participatory research addressing constraints related to systems diversification and improvement and agro-ecological intensification. In this regard, the project is funding several graduate students to conduct their MSc thesis research within the project to build capacity and to acquire valuable practical field experience concurrently.


Farm Household

(i)Soil system component

(Fertility enhanced)

(ii)Crop system component

(Yields improved)

(iii)Livestock system

component(Improved productivity)

Market system (Improved income)

(iv)Processing & value

addition

Quality Crop residues

QualityFodder

N-fixation enhanced to supplement inorganic N

Farmer training: utilization & value addition (grain, milk, vegetables, etc.)

Grains & vegetables

Improved nutrition: grain, milk, vegetables, etc.

High quality legume biomass, e.g. Lablab, soybean, etc. to soil directly or via manure (trade-off)

Surplus & value-added products for additional household income

Legumesintroduced

Improved yields-N-fixation-Weed control

Improved output of crop & livestock products

Improved environmental services, e.g. N-fixation, Carbon sequestration, etc.

High quality manure to enhance soil fertility

Higher qualityManure

Figure 1. A diagram of the typical Nandi Production system, system interactions, feedback, and the proposed interventions to improve system productivity.

Inputs

Quality Crop residues

P (Rock –P) fortification of manure

N a

nd P

fert

ilize

rs fo

r soi

l fer

tility

im

prov

emen

t

Changes in pest & disease dynamics

Figure 1. The project theory of change


II. Narrative The Western Kenya smallholder systems are characterized by a high level of biophysical and socio-economic variability. As a result, responses to options being tested are often difficult to follow and generation of appropriate recommendations rendered a complex exercise. The dominant sources of the biophysical and socio-economic variation need to be factored into the design and implementation of research in smallholder systems. Therefore, during the mid-year review meeting of 2012 the project made steps towards achieving this by developing hypotheses to guide project implementation as well as performing additional characterization of the sites using GIS techniques. Overall Project Hypothesis: the project can identify the dominant sources of variation influencing adaptability and acceptability of legumes in each project site using biophysical & socio-economic characterization. Several site-level hypotheses were also formulated: Koibem site: market orientation is the main factor driving legume acceptability whereas variable soil fertility is the main factor driving productivity of the adapted legumes. Kapkarer site: food security, soil improvement, striga suppression and marketability are the key drivers of farmer acceptability of legumes while tolerance to soil-borne pests & diseases is the key factor influencing adaptability. Kiptaruswo site: higher incidence of legume pest and diseases at Kiptaruswo limits the productivity and utilization of legumes by farmers. In 2013, research activities focused on testing some of these hypotheses. Where necessary, new activities were initiated, while in other cases on-going activities were re-oriented and data collection streamlined to address the hypotheses. For example, in Kapkerer where food security and Striga suppression were hypothesized to legume acceptance, verification trials were initiated to test capacity of selected grain legumes to address soil fertility, food security and suppress Striga. In contrast, in Kiptaruswo site where high incidence of pests and diseases was hypothesized to influence legume acceptance, no new trials were initiated because on-going trials were deemed adequate to address the hypothesis. Verification trials (Activity 1d) This activity was established to verify the capacity of the grain legumes promoted by the project to suppress striga and improve soil fertility in small holder farming systems and was in response to observation by farmers that plots previously planted with legumes had relatively lower striga emergence when maize was planted in the following season than plots that had continuous maize. Farmers also observed that maize performed better in plots previously planted with grain legumes, an effect likely to improve household food security situation. Grain legume-maize rotation trials were conducted at three sites (Kapkerer, Kiptaruswo and Koibem). Legumes were established in September 2012 (short rain season) followed by maize in March 2013 (long rain season).The grain legumes evaluated were groundnuts (CG7), soybean (SB19), lablab (RONGAI) and bean (control treatment) in 16m2 plots. A total of 37 farmers participated in the trials as follows: 18 in Kapkerer, 12 in Kiptaruswo and 7 in Koibem. Farms selected for the trials were those with high striga infestation. Striga is generally confined to Kapkerer site. However in Kiptaruswo and Koibem where striga is not a major production constraint, the trial focused on establishing the soil fertility improvement capacity of the grain legumes. Data collected during the short rain season (grain legume phase) included: Legume emergence, plants dying of root rot 14, 21 and 28 days after emergence, hallo blight and aphid incidence and severity, plant population at harvest, striga counts at harvest, grain yield and yield parameters. During the long rain season (maize phase) data collected included: maize emergence, striga counts, number of plants showing nitrogen and phosphorus deficiency, and grain yield. Results: The introduced grain legumes showed capacity to suppress striga. This was observed in Kapkerer, where striga suppression was the main focus of the study. Overall, bean-maize rotation


had the highest mean number of striga plants per plot (112), soya-maize had 88, groundnut-maize had 71 and lablab-maize had 58.The grain legumes also had influence on soil fertility. The grain yield of lablab-maize rotation (lablab-maize) was 2.4 t/ha, groundnut-maize (1.8 t/ha) compared with the grain yield of the control treatment (bean-maize) of 1.3 t/ha. Way forward: Since this trial has been run for only one year, hence there is need to repeat it in 2014 to confirm these results before being scaled out by the NGOs and CBO partners in the project. Varietal screening (Activity 2 a) The small holder farming systems of Nandi are dominated by bean as main grain legume under cultivation. The consequent build up of pests and diseases has negatively affected bean production. There is need for introducing other grain legumes to diversify the system to reduce pest and disease pressure. Apart from reducing pest and disease pressure, the new legumes will also provide benefits such as enhanced soil fertility, food security, house hold income generation and fodder. This activity was therefore initiated to assess the adaptability of a number of promising alternative multipurpose grain legumes and to determine whether they can be sustainably used in the system to provide the above benefits. Six multipurpose legume species (with three varieties per species) were screened in three project sites (Kapkerer, Kiptaruswo and Koibem) in the short rains 2012 and long rains 2013. These were soybean (SB25, SB19, Gazelle), cowpea (M-66, K-80, KVU27-1), lablab (Rongai, TX-24, 11630), ground nut (99568, 89749, CG-7), field pea (Green feast, Ambassador, Cascadia), bean (KK071, KK072, KK15). The experimental design was split plot with 1 replicate per farm. Plot size was 4m2, triple super phosphate fertilizer was applied at planting at the rate of 30kg P/ha. Data was collected on plant stand at (14, 21 and 28 days after planting), plant survival, pests and diseases (root rot / bean fly), days to 50% flowering, nodulation, foliar pests and diseases, number of pods per plant/ seeds per pod, plant stand at harvest, grain yield and biomass accumulation. Results:Groundnut, soybean and lablab showed the greatest potential. Overall, groundnut performed best based on yield, pest and disease tolerance, income generation and soil fertility improvement. Variety CG7was best across the sites. For example, in long rain 2013, the grain yield of CG7 was 3.4 t/ha in Kapkerer, 1.0 t/ha in Kiptaruswo and 1.6 t/ha in Koibem. This good performance is consistent with those obtained in previous four seasons of screening. In comparison, the best performing soya variety across the sites was SB19 with 1.69 t/ha in Kapkerer, 0.78 t/ha in Kiptaruswo and 1.37 t/ha in Koibem. For lablab, the best performing variety in Kapkerer was TX24 (0.77t/ha), while in Kiptaruswo and Koibem 11630 had the best performance with a grain yield of 0.68 t/ha and 0.65 t/ha, respectively. CG7 and 89749 were tolerant to leaf spot consistently in the previous four seasons where as SM 99568 was tolerant to rosette virus but susceptible to leaf spot. Halo blight is the most important disease of lablab, however variety TX24 showed resistance to the disease in Kapkerer, where the pressure of the disease was highest during the two seasons of screening. The three groundnuts variety screened showed great potential for soil fertility improvement; this was assessed based on nodulation capacity and biomass accumulation, during short rain 2012 and long rain 2013 seasons. However variety CG7 was the best in nodulation and biomass accumulation across the sites. For example in short rain 2012 season, variety CG7 had a mean of 274 nodules per plant in Kapkerer, 167 nodules per plant in Kiptaruswo and 168 nodules per plant in Koibem. Biomass accumulation followed the same trend- 1.27 t/ha in Kapkerer, 2.66 t/ha in Kiptaruswo and 2.84 t/ha in Koibem. Nodulation and biomass accumulation performance by soybean and lablab was equally good. CG7 showed the greatest potential to contribute to household income generation. Variety CG7 is high yielding has good seed size and color. These are good market attributes. Participating farmers have been selling groundnut at 150 Kenya shillings per kg compared with 90 Kenya shillings for bean, which is the common grain legume in most of the households. Soybeana and lablab sell at 100 Kenya shillings per kg. Lablab has the highest fodder value among the grain legumes introduced in the farming system. In short rain 2012, lablab variety


RONGAI had a mean biomass accumulation of 12.5 t/ha in Kapkerer, 8.7 t/ha in Kiptaruswo and 12.1 t/ha in Koibem. Part of this biomass is being fed to livestock as fodder. Farmers have been reporting increases in milk production of up to 25%. Assessment of lime and phosphorus as factors for optimal legume growth (Activity 2 b) The project hypothesized that soil fertility is the main factor driving productivity of the adapted legumes in the project sites where soil fertility is poor. The poor performance of the legumes in certain cases suggested deficiency of some essential soil nutrients. In this activity, the effect of lime and phosphorus was assessed on the productivity of two selected grain legumes: bean (KK8, KK15) and soybean SB 19. The trial was initiated in September 2012 in Kiptaruswo (medium-low fertility) and Koibem (high fertility) for comparison. The experimental design was randomized complete block with a single replicate per farm and 5 farms per site. The treatments were triple superphosphate applied at 30kg P/ha, lime at 2 t/ha, and untreated control. All the legume seeds were inoculated with biofix. Data was collected on emergence, plant stand at 21 and 28 days after planting, plant height and nodulation at 50% flowering, biomass accumulation, and grain yield and yield parameters at harvest. Results: TSP and lime had positive yield impacts on most of the farms compared to the untreated control. The responses to lime or TSP varied with site, species and variety. Lime was more effective than TSP for soybean, TSP was more effective than lime for KK15 at Koibem, and lime had greater impact in Kiptaruswo than Koibem. In general for the most of the variables, lime had a greater impact than TSP especially at Kiptaruswo for soy bean and KK15. The higher response to lime suggests that some other mineral nutrient (other than P) is limiting yields (Ca, Mg, Fe, and Al, Mo). Way forward: The results drawn are tentative as more data is needed to substantiate these observations. In 2014, additional comparison plots will be set up in Kiptaruswo and Kapkerer sites where soil pH is low and yields are lower compared to Koibem, to confirm these results. Bruchids control experiment (Activity 2e) Extensive damage to stored legume grains, particularly bean and lablab, has been observed in a number of farms in the project sites. Apart from negatively impacting household food security, the holes made on the grains by these storage pests lower the market value of the grain. This activity was therefore initiated in September 2012 to identify a range of low cost storage pest control strategies that are easy to use, affordable, non-toxic and accessible to farmers. Treatments were wood ash, solar sterilization, and two controls-Actelic and untreated check, applied to either maize or bean in sample bags. Over a three month period, two batches of 100 grain samples were drawn at monthly interval to count the number of exit holes, number of bruchids/weevils present (dead or alive) and number of visible eggs on the grains using magnifying glass. Treatments were ranked on effectiveness, affordability, availability, and ease of use. The ranking criteria was 1= not effective, 3= moderately effective and 5= effective. Results: Bruchids were much less important across the sites than earlier expected. This is likely due to low temperatures at Koibem and Kiptaruswo, as bruchid development ceases below 20 degrees C. Maize grain recorded more post-harvest losses than beans, particularly in the zero control and wood ash treatments. Although Actellic was the most effective treatment, farmers did not rank it highly due to its cost, inaccessibility and worries about toxic residues in the food. Wood ash was fairly effective but in cases where the ash and/or grain were not dry, the treatment caused grain discoloration (reduction in grain quality). Farmers proposed using ash from bean trash because this is used locally as a food tenderizer when cooking vegetables. Solar sterilization performed very


well except where there was insufficient sunshine for 2 hours. In long rains 2013, the results did not indicate clear treatment effects hence it was difficult to draw conclusions. Way forward: These results suggest that it may be useful to conduct a survey to collect information on smallholder farmers’ knowledge on storage pests and methods used to control them. This will establish the magnitude of storage pest problem and the effectiveness of the control strategies available to farmers, to inform further research. Assessment of the seasonal activity, diversity and abundance of destructive insect pests (Activity 2i) Pests and diseases present a major challenge to legume production in small holder farms in western Kenya. The project hypothesized that tolerance to soil-borne pests and diseases is a key factor influencing legume adaptability and productivity in project sites, particularly in Kiptaruswo and Koibem. In this activity, the seasonal activity, diversity and abundance of two pest-chafer grubs and aphids were investigated. a) chafer grubs: Smallholder farmers had observed high mortality of the seedlings (bean and soybean) in newly introduced legumes due to chafer grub damage. There is a great deal of diversity among the chafer grubs and the specific destructive species can only be easily identified from the adult beetle. Based on this identification, the necessary control measures can then be formulated. This activity was conducted to provide information on the seasonal activity, diversity and abundance of beetles related to the destructive chafer grubs. Insect traps were mounted in all the three sites, the adult beetles trapped were sorted into different categories using morphological characteristics. From the sorting, the beetle species that are responsible for the destructive chafer grub have been identified. Challenges: Even though it was possible to identify the adult beetles responsible for destructive chafer grubs, it is difficult to determine the species these beetles belong to using only morphological characteristics. However, the data collected so far gives us a better understanding of the diversity, abundance and seasonal calendar of the beetles, upon which control strategies can be formulated. This activity has been terminated. b) Aphids:Black bean aphids (Aphis fabae scop.) and the viruses they transmit are among the key biotic constraints contributing to low bean yields in south Nandi. This activity assessed the incidence and severity of bean aphid in relation to two bean root rot tolerant varieties (KK8 and KK15) and two local bean varieties (Alulu and Punda) in three farms in each project site (Kapkerer, Kiptaruswo and Koibem). The abundance and diversity of aphid natural enemies in the trial sites was also assessed. Data was collected on plant stand counts (7, 14, 21, 28 days after planting), number of winged aphids and natural enemies caught on 2 yellow sticky cards per plot the cards were placed at growth stages V4 and R7. Destructive sampling of 10 plants per plot was done at 50% flowering to assess total number of aphids and mummies. Grain yield was determined at harvest. Challenges: Low aphid incidence was recorded during the short rains 2012 and long rain 2013 seasons and it was therefore not possible to draw conclusions from this trial. The low incidence of aphids may be an indication that aphids may not be a major constraint to legume productivity in the project sites. More observation is necessary to determine the way forward. Scaling-out of promising legume technologies by NGO’s (Activity 3) The project is working with one CBO (Avene) and two NGOs (ARDAP and REFSO) to out-scale successful legume technologies in other parts of Western Kenya beyond the project implementation sites. This part of the report summarizes the progress made by these partners. Avene: targeted to scale out promising grain legumes to a total of 300 farmers spread out in 4 locations of Vihiga County (during short rains 2012 and long rains 2013). These locations were Wodanga, North Maragoli, and Busali East and West. The grain legumes that were promoted were


the ones that had undergone screening in the varietal screening trials and participatory evaluation by farmers in Nandi South project sites. These included soy bean SB19, lablab –Rongai, and bean varieties KK15 and KK8. In order to obtain sufficient seed to meet the target of 300 farmers, Avene hired land to produce assorted seeds of grain legume varieties. About 70 kg of assorted seeds were produced during short rains 2012. In the long rains 2013, 60 kg of seed were produced. Farmers targeted for out-scaling were those that experiencing food insecurity and had shown interest in trying out new grain legumes. Each target farmer was given 0.3 kg of assorted grain legume seed for trying out. They were trained on legume management e.g spacing, planting and soil fertility management. Farmers were to conduct their own evaluation and determine which varieties to up-scale, relying on their own bulked seed or on seed from community based producers. The target set by Avene of reaching 300 farmers with seed and legume management training were achieved. 80 farmers were reached in Busali East, 50 in Wodanga, 110 in North Maragoli and 60 in Busali West locations of Vihiga County. With the amount of seed given, farmers were able to plant 16 m2 plot of land and they have been able to scale up to 400m2. Way forward: To intensify seed production so that we can reach more farmers in preceding seasons. ARDAP: Ardap targeted to scale-out grain legume technologies to 130 farmers during the year. The legumes selected for scaling-out were bean (varieties KK8, KK15 and KK071) , groundnut variety CG7, soya bean variety SB19 and lablab variety Rongai. The 130 farmers were targeted in Butula district, Busia County. The organization leased 2 acres of land for bulking the seeds of the legume varieties targeted for out-scaling. A total of 55 farmers (35 males and 20 females) were trained on various aspects of legume management. ARDAP and farmers conducted participatory evaluation of legume performance. The target of 130 farmers was achieved and the legume seeds of the varieties mentioned above were distributed to farmers for evaluation and up-scaling. REFSO: the target was to reach out to at least 600 farmers who were members of various farmer groups in 6 locations (Chakol, Angorom, Asinge, Apegei,Ochude and Apatit) in Busia County during the short rains 2012 and long rains 2013.The legumes promoted were soybean varieties SB19 and SB20, bean varieties KK15, KK8, KK071, and Lumbuku, a land race. The required legume seed to support the scaling out exercise was bulked by the farmer groups themselves. Every famer group gave about 4 kg of assorted legume seed to each member to start with. Training on good agronomic practices was given by REFSO to each farmer group involved. These groups were followed on regular basis to assess progress being made. The scale out exercise went on well during the 2 seasons. Out of the target of 600 farmers, 754 were reached with grain legumes. Most of the farmers have scaled up by moving from small demo plots to ¾ acre plots. Farmers are planting either pure stand or intercropped with maize or sorghum.


III. ANNUAL YEAR 4 WORKPLAN (2014)

Objective

Activity details

Jan Feb March April May June July Aug S= Oct Nov Dec Long rains Short rains

1. Participatory analysis & Improvement activities

Budget: USD:

a. Annual Researcher workshop

XXX

b. In-season exchange visits Farmer-to-farmer exchange visits between four trial sites (Koibem, Kiptaruswo, Kapkerer & Vihiga)

XXX XXX XXX XXX

c. Verification trials i. Selection of farms, characterization, laying of plots and planting ii.data collection and analysis (James, Ojiem)

xxx

xxx

xxx xxx

xxx

xxx

xxx

xxx xxx

xxx xxx

xxx

XXX

2. Experiments & Assessments Budget: USD:

a. Varietal screening & socio- economic assessment of grain legume species & cultivars i) Refine list of legumes for

screening & source seed of additional bean varieties (Ojiem)

XXX

ii) Plot layout, planting & data collection (Kamwana), assistance on pathogens identification (Muthomi, Beth)

XXX XXX XXX XXX XXX XXX XXX XXX

b. Continue site characterization using GIS tools of selected farms

i) Biophysical characterization: determine variability in temperature, rainfall,altitude (Ojiem) ii) Socio-economic characterization: household surveys in project sites (Oketch)

XXX XXX

XXX XXX

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Activity Details Jan Feb March April May June July Aug Sept Oct Nov Dec 2. Experiments & Assessments cont.

b.Lime trial Selection of farms, trial layout, planting and data collection

XXX XXX XXX XXX XXX XXX XXX XXX XXX

c. P fortification of compost Train farmers on compost

manure quality improvement. (Egerton Student)

XXX XXX XXX XXX XXX XXX XXX XXX XXX

d. Investigate seed dressing options in control of bean root rot and bean fly in legumes Selection of sites, trial layout,

planting, data collection and analysis (University of Nairobi Student)

XXX XXX XXX XXX XXX XXX XXX XXX XXX XXX

3. NGO’s , CBO’s & farmer group activities Budget: USD:

a. Scale-out promising technologies through NGO, CBO and farmer group activities Avene, REFSO & ARDAP conduct demonstrations of promising technologies and bulk seed for use in scaling-up activities (Josephat, Michael & Boniface)

XXX

XXX

XXX

XXX

XXX

XXX

XXX

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b. Seed production, business & marketing training for seed producer groups in South Nandi Train and work with community- based seed producers to bulk seed of new legume species (Janet, Josephat)

XXX

XXX

XXX

XXX

XXX

XXX

XXX

XXX

XXX

4. Collaborator capacity building Budget: USD:

a. Annual mid-year collaborator meeting Collaborator attend a 3 day meeting to assess and review project plans and progress (Ojiem)

XXX

b. CoP meeting Collaborators attend annual CoP meeting (Ojiem)

XXX

c. Data analysis and publication workshop

XXX

V. Appendices Appendix A: Research reports

INFLUENCE OF LABLAB RESIDUES ON INCIDENCE AND

SEVERITY OF ROOT ROT AND YIELD OF BEAN INTERCROPPED WITH MAIZE

Mugambi1, I. K., Muthomi1, J. W., Ojiem2, J., Chemining’wa1, G. N. and Nderitu3, J. H. 1. Department of Plant Science and Crop Protection, University of Nairobi 2. Kenya Agricultural Research Institute (KARI), Kibos 3. Mount Kenya University

ABSTRACT Lablab (Dolichos lablab L.) is green manure crop used in soil fertility management. However, the effect of the residues on the severity of soil-borne pathogens is not well understood. This study was carried out to investigate the effect of incorporating lablab residues on bean root rot and yield. Lablab residue management methods included incorporation over the whole plot, residues placed between rows of beans, residues removed from the plot plus application of DAP fertilizer and residues removed from the plot without fertilizer application. Four bean varieties used were KK8, KK15, KK072 (tolerant to root rot) and GLP2 (susceptible to root rot). The experiment was carried out at two agroecologically and fertility diverse sites Incidence of root rot and chafer grub was determined at early growth stages while biomass and yield of both maize and beans were determined at harvest. High root rot incidences of up to 40% was observed where the lablab residues were cut and removed for the susceptible GLP2 bean variety in low fertility site. All the bean varieties showed high levels of infection in the stem bases but KK15 and KK8 bean varieties showed tolerance to infection. Significantly higher incidences of chafer grubs of up to 50% were observed in plots where lablab residues were scattered and incorporated over the whole plot. Bean variety KK15 had highest yield while highest biomass was obtained in plots where lablab residue was removed and DAP fertilizer applied. The results indicate that incorporation of lablab residues improved bean crop yields and crop biomass without significant increase in root rot damage. Uniform incorporation of the residues resulted in better crop performance and the beneficial effect was more pronounced in low fertility site. The performance enhancing benefits of the residues were also observed in the accompanying maize intercrop maize. Key words: chafer grub, intercropping, maize, Phaseolus vulgaris, root rot complex, yield

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INTRODUCTION Common bean (Phaseolus vulgaris L.) is an important source of dietary protein and component of production systems among resource-poor farmers especially in the developing countries (Katungi et al., 2010). Root rot mainly caused by Fusarium species is a major constraint to bean production in the tropics. These fungi occur in soil and organic matter as saprophytes or in a form capable of causing disease, mostly in a complex with other root rot fungi (Waller and Brayford, 1990). They mainly attack plants that have been weakened by chafer grubs (Phyllopertha horticola), bean flies (Ophiomyia phaseoli), nematodes and other pests (Medvecky et al., 2007). Agronomic practices such as crop rotation, planting of fallow crops and application of organic amendments have led to changes in soil structure and root rot disease dynamics (Bailey and Lazarovits, 2003). These practices lower inoculum density in the soil, deprive the pathogen of its host and create conditions that favor the growth and development of microorganisms antagonistic to the pathogen (Peter et al. 2009; Meenu et al. 2010). Leguminous crop residues and green manures improve soil fertility, increase nutrient supply in the soil through biological nitrogen fixation and improve soil structure (Toomsan et al., 2000). They however increase the abundance of root rot feeding chafer grubs (Medvecky et al., 2006). Lablab purpureus is a leguminous crop rich in nitrogen and useful as an organic amendment due to properties such as high biomass production, rapid establishment and its soft stem which makes it easy to chop prior to incorporation (Mureithi et al., 2003). Farmers in Western Kenya have been introduced to new green manure legumes for soil fertility enhancement but little is known about the effect they have on soil-borne pests and diseases (Medvecky et al., 2007). This study therefore aimed to determine the effect of lablab residues on soil borne bean diseases.

MATERIALS AND METHODS

Experimental site The experiment was carried out in Koibem and Kapsengere sites in Nandi South district. Koibem is high fertility while Kapsengere is low soil fertility area, based on the time since the land was opened from Kakamega forest for cultivation (Nyberg et al., 2012). Koibem area has been under cultivation for 5-30 years while Kapsengere has been under cultivation for 80-105 years (Odundo et al., 2010). Nandi South district lies within latitudes 0° and 0°34’’ North and longitudes 34°44’’ and 35°25’’ East at an elevation of 1850-2040 m above sea level (Nyberg et al., 2012). Annual precipitation is 1200 mm to 2000 mm with temperature ranging from 18˚ to 25°C and soils are mainly well drained clay-loams, classified as Nitosols (FAO-UNESCO, 1997). The district’s main agro ecological zones are upper highlands (UH) covering about 5%, lower highlands (LH) 24% and upper midlands (UM) 56% (FAO, 2007).

Experimental design and layout At both experimental sites Koibem (high soil fertility) and Kapsengere (low soil fertility), lablab variety Rongai was planted during the short rains of the year 2011 at a spacing of 45 cm x 30 cm, allowed to grow until flowering when the vegetation was harvested and residues used for

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incorporation into the soil during the subsequent long rain season of the year 2012 when beans were intercropped with maize. The vegetative mass of the lablab crop was harvested, the vines chopped into small pieces for ease of handling during incorporation and oven dried to constant weight. The lablab residue management treatments were: Lablab incorporated over the whole plot, lablab residues placed between rows of beans, lablab residues cut and removed from the plot, lablab residues cut and removed from the soil and DAP fertilizer applied at recommended rate. Equal amounts of the chopped lablab biomass were weighed and applied to the appropriate plots measuring 5 m x 4 m, at the rate of 50 kg/ha. In each of the lablab residue management option plots, the following four bean varieties were planted: KK8 (tolerant to root rot), KK15 (tolerant to root rot), KK072 (tolerant to root rot and bean fly) and GLP2 (susceptible to root rot and bean fly). Each bean variety was planted on 5 m x 4 m plots intercropped on the same row with maize at a spacing of 75 cm x 15 cm, between and within rows respectively. Maize was planted at a spacing of 75 cm by 30 cm. The plots were separated by 1m paths and the treatments laid out in a randomized complete block design with split plot arrangement. Bean variety comprised the main plots and lablab residue management the subplots such that there were four main plots per block and each main plot was divided into four subplots. The sixteen treatment combinations were replicated three times in three blocks. Within each main plot the residue management methods were assigned at random to the sub plots. Agronomic practices such as weeding were carried out as required. Data collected included crop emergence, incidence of root rot, bean fly and chafer grub infestation and damage, plant stand, plant height, dry matter and seed yield. Incidence of foliar diseases was determined as necessary.

Assessment of root rot incidence Incidence of root rot infected bean plants was determined by counting the number of plants showing root rot symptoms per plot at the second, fourth and sixth week after emergence. Root rot infected plants were identified based on symptoms such as yellowing of leaves, wilting, stunted growth, death and brown discoloration on the roots.

Assessment of yield and yield components Variation in agronomic performance of the bean crop was observed by taking yield parameters such as dry matter, number of pods per plant, number of seeds per pod and total seed yield. This was extrapolated to kg/ha. At pod maturity, ten plants were randomly selected from each plot and the number of pods per plant counted. The harvested pods from the sampled plants were shelled and seeds counted for each plant. The average number of seeds per plant was divided by the average number of pods per plant and expressed as the average number of seeds per pod. Bean biomass at harvest was weighed for each plot. Performance of the maize crop was determined by taking yield parameters such as total biomass, cobs per plot, rows per cob, cob length and seed yield.

Data analysis All data was subjected to analysis of variance (ANOVA) using Genstat software version 7.1 (Payne et al., 2008) and means were separated using Student- Newman-Keuls (SNK) test at P=0.05. Poisson regression model was used for count data.

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RESULTS

Effect of lablab residues on root rot incidence The mean root rot incidence was insignificantly different in the two sites (p=0.8787). However, there was an interaction effect between the variety and site and also between management method and the site. Removal of lablab residues led to significantly higher incidences of root rot in Kapsengere while in Koibem there were no significant differences among the treatments.GLP2 had the highest root rot incidence in Kapsengere, but in Koibem there was no significant difference among varieties (Fig 1).

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Figure 1: Percentage root rot incidence on four bean varieties under different lablab residue management methods in Kapsengere and Koibem in Nandi South

Effect of lablab residues on chafer grub incidence There was a significant interaction effect between variety and residue management method (P=0.005). Treatments where lablab residues were uniformly incorporated over the whole plot had the highest chafer grub incidence in Kapsengere, and treatments where the residues were removed and where they were removed and fertilizer applied the lowest. There was no significant difference among the treatments in Koibem (Table 1). There was a higher incidence of chafer grub in Kapsengere than Koibem. GLP2 had the highest incidence of chafer grubs under all treatments and KK15 and KK8 the lowest. In addition, infection by chafer grubs enhanced root rot disease.

Table 1: Percentage Chafer grub incidence under different residue management methods in two

sites in Nandi south

Site/Variety Incorporated Btn rows Removed Removed+DAP Mean

Kapsengere

GLP2 3.7 2.8 1.6 1.9 2.5

KK072 2.3 1.6 1.2 1.9 1.8

KK15 2.6 0.4 0.0 0.0 0.8

KK8 0.8 1.7 0.4 0.0 0.7

Mean 2.3 1.6 0.8 1.0 1.4

Koibem

GLP2 2.8 3.0 1.3 2.1 2.3

KK072 1.4 1.4 0.5 0.6 1.0

KK15 0.0 0.0 0.0 0.0 0.0

KK8 0.4 1.6 0.0 0.4 0.6

Mean 1.1 1.5 0.4 0.8 1.0

LSD V x Mgt =0.7, CV (%) =49.5

LSD: Least significant difference at 5% level, CV: Coefficient of variation, Btn: between, DAP: Diammonium phosphate, Mgt: Management,Var: Variety

Effect of lablab residues on bean seed yield and biomass The interaction of variety and residue management method was significant (P=0.002) for bean seed yield. In addition, significant differences were observed among the varieties and residue management methods. Removal of lablab residues and application of fertilizer led to the highest bean yield in both sites (Table 3 and 4). However, the lowest yield in Kapsengere was in the treatment where lablab residues were removed. There was no significant difference in the other

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three treatments in Koibem.GLP2 had the lowest yield in Kapsengere with KK8 and KK15 yielding the highest. In Koibem, GLP2 and KK072 had the lowest yield while KK15 had the highest. Kapsengere site produced a significantly higher seed yield than Koibem (P=0.03). The interaction between variety and residue management method was highly significant (P<0.001) for biomass at harvest. In addition, significant differences were observed among the varieties and residue management methods. GLP2 had the lowest biomass in Kapsengere, while the other three varieties were not significantly different. The highest biomass in both sites was recorded where residues were removed and fertilizer applied, while the lowest was in plots where residues were removed. There was a significant positive correlation between biomass and seed yield in both sites. Root rot significantly reduced bean seed yield and biomass in both sites (Table 3 and 4). Table 2: Root rot and chafer grub incidence, bean seed yield and biomass under different lablab

residue management methods

Lablab residue management method Site/Variety Incorporated Btn rows Removed Removed+DAP Kapsengere Root rot 8b 7b 17a 6b Chafer grub 2a 2a 1b 1b Biomass 157.1b 126.5bc 108.8c 267.0a Seed yield 245.0b 213.9b 155.8c 318.7a Koibem Root rot 11a 12a 9a 7a Chafer grub 1b 2a 0c 1b Biomass 161.1bc 176.8b 145.0c 239.0a Seed yield 153.8ab 142.0b 120.8b 192.6a Values followed by different letter(s) along samerow are significantly different (P≤0.05)

Table 3: Root rot and chafer grub incidence, bean seed yield and biomass for different bean

varieties

Bean variety Site/Variety GLP2 KK072 KK15 KK8 Kapsengere Root rot 20a 7b 8b 4b Chafer grub 3a 2b 1c 1c Biomass 33.0c 172.6b 213.8a 239.9a Seed yield 51.8c 216.8b 351.3a 313.4a Koibem Root rot 15a 13a 5b 7b Chafer grub 2a 1.0b 0.0c 1b Biomass 82.4c 110.3c 329.2a 200.0b Seed yield 41.9c 53.8c 408.3a 105.1b Values followed by different letter(s) along the same row are significantly different at 5% level of probability

Effect of lablab residues on maize yield Residue management method was highly significant (P<0.001) for maize cob weight. The highest cob weight in both sites was recorded in plots where DAP fertilizer was applied, followed by plots

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where lablab residues were incorporated over the whole plot and where they were placed between rows of bean. Removal of lablab residues led to the least cob weight in both sites (Figure 2). Residue management method was highly significant (P<0.001) for stover biomass. Addition of fertilizer led to the highest stover biomass in both sites, while removal of lablab residues led to the lowest stover biomass. There was no significant difference between treatments where lablab residues were incorporated uniformly over the whole plot and where DAP fertilizer was applied in Kapsengere (Figure 2). Koibem produced a significantly higher cob weight and stover biomass than Kapsengere.

Fig 2. Maize stover and cob weight per plot (Kgs) under different lablab residue management

methods in Kapsengere (low fertility) and Koibem (high fertility) sites in Nandi south

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DISCUSSION Removal of lablab residues led to the highest root rot incidence while the application of fertilizer led to the lowest incidence, with more clear differences observed in the low fertility site. This is in agreement with other published reports (Medvecky et al., 2007, Abawi and Widmer, 2000, Peters et al., 2003 and Okoth and Siameto, 2010) who found that organic matter increases soil fertility and this leads to lower root rot incidence. Inorganic fertilizer improves the vigor of the crop and therefore enables it to overcome the effects of the root rot pathogens (Duffy and Defago, 1999). However, Medvecky et al., (2007) also found that retention of lablab residues increased Pythium seed infection.

Treatments where lablab residues were uniformly incorporated over the whole plot had the highest chafer grub incidence in both sites and those where residues were removed the lowest. This agrees with Medvecky et al., (2006); (2007) who found out that lablab residues increased chafer grub incidence due to increased soil fertility and favorable conditions for oviposition and grub survival. This effect is however countered by the improved vigour of the crops (Abawi and Widmer, 2000). The results of this study show that application of fertilizer led to the highest bean seed yield and biomass at harvest in both sites. This was closely followed by the uniform incorporation of residues over the whole plot. Removal of lablab residues led to the lowest bean seed yield and biomass and this was clearer in the low fertility site. These results agree with Belachew and Abera (2011) and Shah et al., (2011) who found out that green manure significantly increased wheat yield relative to the control, and that the removal of residues led to the lowest yield due to lack of sufficient nutrients. Lablab residues have a nutrient composition of 3.2% N, 0.21% P, 1.57% K and 0.2% Mg (Lelei, 2004; Nworgu and Ajayi, 2005) and therefore the increase in soil nutrient status which led to an increase in yield. However, Mureithi et al., 2003 and Tolanur (2009) found out that the use of organic together with inorganic fertilizers increased grain and straw yield of chick pea without deterioration of soil quality. This integrated nutrient management method is an ecologically sustainable way of increasing bean yield for small scale farmers. Treatments where DAP fertilizer was applied had the highest cob weight and stover biomass, followed by treatments where lablab residues were uniformly incorporated over the whole plot. Removal of lablab residues led to the least stover biomass and cob weight. This is due to depletion of soil nutrients and decrease in pH (Mureithi et al., 2003; Medvecky et al., 2007; Nyambati et al., 2009). These results conform to findings of studies done by Ayuke et al, (2004), Njeru et al., (2007) and Odhiambo (2011) which showed that green manure and plant residues increase maize yield comparably to inorganic fertilizer. Organic amendments increase soil microbial activity and improve soil structure, and this results to higher yields.

REFERENCES

Abawi and Widmer 2000. Impact of soil health management practices on soil borne pathogens, nematodes and root diseases of vegetable crops. Applied Soil Ecology, 15, 37-47.

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Ayuke, F., Rao, M., Swift, M., Opondo-Mbai, M. 2004. Effect of organic and inorganic nutrient sources on soil mineral nitrogen and maize yields in Western Kenya. Managing Nutrient Cycles to Sustain Soil Fertility in Sub-saharan Africa, 65, 97.

Bailey, K and Lazarovits, G. 2003. Suppressing soil-borne diseases with residue management and organic amendments. Soil and Tillage Research, 72, 169–180.

Belachew, T and Abera, Y 2011. Effect of green manuring in combination with Nitrogen on soil fertility and yield of bread wheat (Triticum aestivum) under double cropping system of Sinana-dinsho, Southeast Ethiopia. Journal of Biodiversity and Environmental Sciences, 1, 1-11.

Bulluck, L., Brosius, M., Evanylo, G., Ristaino, J. 2002. Organic and synthetic fertility amendments influence soil microbial, physical and chemical properties on organic and conventional farms. Applied Soil Ecology, 19, 147-160.

Duffy, B., Defago, G. 1999. Macro- and micro element fertilizers influence the severity of Fusarium crown and root rot of tomato in a soilless production system. Hortscience, 34, 287-291.

FAO Kenya, 2007. Food security profile for 23 districts.

FAO-UNESCO, 1997. Soil Map of the World. Revised Legend, edited by ISRIC, Wageningen.

Katungi, E., Farrow, A., Mutuoki, T., Gebeheyu, S., Karanja, D., Alamayehu, F., Sperling, L., Beebe, S., Rubogoyo, J., Buruchara, R. 2010. Improving common bean productivity: An analysis of socio-economic factors in Ethiopia and Eastern Kenya. Baseline report tropical legumes II. CIAT.

Lelei, J. 2004.Impact of soil amendments on maize performance and soil nutrient status in legume maize intercropping and rotation systems in Central Rift Valley province of Kenya. Ph.D thesis, University of Natural Resources and Applied Life Sciences, Austria.

Mahala, A., Amasiab, S., Yousif, M., Elsadig, A. 2012. Effect of plant age on DM yield and nutritive value of some leguminous plants (Cyamopsis tetragonoloba, Lablab purpureus and Clitoria (Clitoria ternatea). International Research Journal of Agricultural Science and Soil Science, 2, 502-508.

Medvecky, B., Ketterings, Q., Nelson, E. 2007. Relationships among soil borne bean seedling diseases, Lablab purpureus L. and maize stover residue management, bean insect pests and soil characteristics in Trans Nzoia district, Kenya. Applied Soil Ecology, 35, 107-119.

Medvecky, B., Ketterings, Q., Vermeylen, F., 2006. Bean seedling damage by root-feeding grubs (Schizonycha spp.) as influenced by planting time, variety and residue management. Applied Soil Ecology, 34, 240-249.

Page 19

Meenu, B., Praveen, K., Satish, L. 2010. Effect of composts on microbial dynamics and activity, dry root rot severity and seed yield of cowpea in the Indian arid region. Phytopathologia Mediterranea, 49, 381-392.

Mureithi, J., Gachene, C., Wamuongo, J. 2003. Legume cover crops research in Kenya. Experiences of the legume research network Project. A synthesis report of Phase 1 research activities.

Ndiaye, M., Termorshuizen, J., Ariena, H. 2008. Effect of rotation of cowpea (Vigna unguiculata) with fonio (Digitaria exilis) and millet (Pennisetum glaucum) on Macrophomina phaseolina densities and cowpea yield. African Journal of Agricultural Research, 3, 37-43

Njeru, C., Okalebo, R., Ojiem, J., Othieno, Lauren, J., Medvecky, B. 2007. Maize-Bean intercrop response to sole and combined organic and inorganic fertilizer application in low and high fertility areas of Nandi South district. Proceedings of the 12th KARI biennial scientific conference.

Nwogu, F., Ajaiyi, F. 2005. Biomass, dry matter yield, proximate and mineral composition of forage legumes grown as early dry season feeds. Livestock reasearch for rural development, 17, 2005.

Nyambati, E., Sollenberg, L., Eilitta, M., Mureuthi, J. 2009. Residual effects of of relay-cropped mucuna and lablab on maize and bean yields in North West Kenya. African Journal of Agricultural Research, 4, 1189-1198.

Nyberg, G., Tobella, B., Kinyangi, J., Ilstedt, U. 2012. Soil property changes over a 120-yr chronosequence from forest to agriculture in Western Kenya. Hydrology and Earth System Sciences, 16, 2085-2094.

Odhiambo, J 2011. Potential use of green manure legume cover crops in smallholder maize production systems in Limpompo province, South Africa. African Journal of Agricultural Research, 6, 107-112.

Odundo, S., Ojiem, O., Okalebo, J., Othieno, C., Lauren, J., Medvecky, B., 2010. Effect of phosphorus on survival, nodulation and yield of cowpea (Vigna unguiculata) varieties across a soil fertility degradation gradient in Western Kenya. World cowpea 2010 conference. 27th September to 1st October 2010, Saly, Senegal.

Okoth, S., Siameto, E. 2010. Suppression of Fusarium species in a maize and beans intercrop by soil fertility management. Journal of Yeast and Fungal Research, 1, 35-43.

Payne, R., Harding, S., Murray, D., Soutar, D., Baird, D., Glaser, A., Webster, R. 2008. Genstat release 11 reference manual, Part 2 directives. VSN International, Hemel Hempstead.

Peter, K., Swella, G., Mushobozy, M. 2009. Effect of Plant Populations on the Incidence of Bean Stem Maggot (Ophiomyia spp .) in Common Bean Intercropped with Maize. Plant Protection, 45, 148–155.

Peters, R., Sturtz, A., Carter, M., Sanderson, J. 2003. Developing disease-suppressive soils through crop rotation and tillage management practices. Soil and Tillage Research, 72, 181-192.

Page 20

Ramteke, A., Shirgave, P. 2012. Study of the effect of common fertilizers on plant growth parameters of some vegetable plants. Journal of Natural Product and Plant Resource, 2, 328-333.

Saremi, H., Amiri, M., Ashrafi, J. 2011. Epidemiological aspects of bean decline disease caused by Fusarium species and evaluation of the bean resistant cultivars to disease in Northwest Iran. African Journal of Biotechnology, 10, 14954-14961.

Saremi, H., Burgess, L. 2000. Effect of soil temperature on distribution and population dynamics of Fusarium species. Journal of Agricultural Science and Technology, 2, 119-125.

Shah, Z., Ahmad, R., Rahman, H., Shah, M. 2011. Sustaining rice-wheat system through management of legumes-Effect of green manure legumes and N fertilizer on wheat yield. Pakistan Journal of Botany, 43, 2093-2097.

Songa ,W, Hillocks, J. 1996. Charcoal rot in common bean with special reference to Kenya. International Journal of Pest Management, 42, 213-219.

Songa, W., Hillocks, R. 1996. Legume hosts of Macrophomina phaseolina in Kenya and effect of crop species on soil inoculum levels. Journal of Plant Pathology, 144, 387-391.

Sweeney, A., Renner, K., Laboski, C., Davis, A. 2008. Effect of fertilizer nitrogen on weed emergence and growth. Weed Science, 56, 714-721.

Tolanur, S., 2009. Effect of different organic manures, green manuring and fertilizer nitrogen on yield and uptake of macronutrients by chick pea in vertisol. Legume Research, 32, 304-306.

Toomsan, B., Cadisch, G., Srichantawong, M., Thongsodsaeng, M., Giller, C., Limpinuntana, V. 2000. Biological nitrogen fixation and residual N benefit of pre-rice leguminous crops and green manures. Wageningen Journal of Life Sciences, 48, 19-29.

Waller, J., Brayford, D. 1990. Fusarium diseases in the tropics. Tropical Pest Management, 36, 181-194.

Wuest, B., Albrecht, L., Skirvin, K. 2000. Crop residue position and interference with wheat seedling development. Soil and tillage research, 55, 175-182.

Zebarth, J., Neilsen, H., Hogue, E., Neilsen, D. 1999. Influence of organic waste amendments on selected soil physical and chemical properties. Canadian Journal of Soil Science, 79, 501-504.

EFFECTS OF P-FORTIFIED COMPOST MANURE ON P-UPTAKE AND MAIZE YIELD IN SMALLHOLDER MIXED FARMING SYSTEM OF WESTERN KENYA

M. A. Okumu1, S. M. Mwonga 1, I M. Tabu1, J. Ojiem2 and J. Lauren3

1Egerton University, Department of Crops, Horticulture and Soils, P.O. Box 536, Egerton 20115, Kenya 2Kenya Agricultural Research Institute, Kibos, P.O. Box 1490, Kisumu 40100, Kenya

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3Cornell University, Department of Crop and Soil Sciences, Cornell University Ithaca, NY 14853

Abstract Maize is one of the major food crops in Kenya. Crop yield realized by farmers is however usually low, because of the inherently low soil fertility and poor management. The soils in western Kenya are characterized by low levels of available phosphorus, high soil acidity and low organic matter. The recommended inorganic fertilizers are too costly and less efficient under the acidic conditions. Compost manure and rock phosphate (RP) are recommended for soil fertility management in these predominantly low input systems. However, compost has low P content while RP has low solubility. P-fortification has the potential of increasing the quality of compost manure as a phosphorus source through enhanced solubilization of RP. An experiment was therefore carried out to determine the effectiveness of P-fortified compost manure on P-uptake and maize yield compared to the commonly used phosphorus sources. A Randomized Complete Block Design (RCBD) experiment replicated three times was set up at three sites in South Nandi District. The treatments included; Control (0 kg P2O5 ha-1), Rock Phosphate (60 kg P2O5 ha-1), Triple Super Phosphate (60 kg P2O5 ha-1), Compost (6 t ha-1), and P-fortified Compost (60 kg P2O5 ha-1). Hybrid maize variety H513 and H614 were used as a test crops in the short rains (SR) and long rains (LR) seasons, respectively. The data collected was subjected to ANOVA and means separated by the Least Significant Difference (LSD) test. P-fortification significantly increased the yield of maize in all the three sites. P-fortified Compost performed as well as TSP, the positive control. In the SR season, P-fortified Compost had a relative agronomic effectiveness (RAE) of 109% compared to 37% and 61% for RP and compost respectively. In the LR season, P-fortified Compost had RAE of 111% compared to 60% for RP and compost. The results indicate that P-fortified Compost manure improves uptake of added P and maize yield, and hence offers small scale farmers a cheaper alternative P source. Key words: Rock phosphate, compost fortification, phosphorus enrichment, acid soils, soil fertility improvement INTRODUCTION Maize (Zea mays L.) is the main staple food crop in Kenya. It is grown in different agro-ecological zones across the country. Western Kenya is the most important region for maize production and comprises 52% of the maize growing area in Kenya. Currently, farmers realize less than 1 ton/ha against the potential yield of about 10 tons/ha (Nekesa et al., 1999). The suboptimal yields are mainly attributed to the inherently low soil fertility and poor management. Soils in the region are acidic with predominantly low levels of phosphorus and organic matter contents (Okalebo et al., 2003 and Kinyangi, 2008) The low fertility coupled with poor nutrient management is often reflected in maize yield decline over the years. Small-scale farms in South Nandi District in western Kenya are characteristic of the challenges faced in soil fertility management in the region. The farms have been under cultivation for periods ranging from as little as 15-30 years to over 100 years since conversion from forest and often with inadequate nutrient replenishment and soil fertility management (Kimetu et al., 2008).

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Phosphorus is one of the major nutrients limiting crop production in the region (Kihara and Njoroge, 2013). The inherently acidic soils with high P-fixation in South Nandi present a big challenge to crop production. The inorganic fertilizers are too expensive for the mostly resource poor small-scale farmers and also less effective. The recommended low cost and locally available P sources include Rock Phosphate and compost manure (Mtengeti et al., 2013). Rock Phosphate is however limited in solubility while compost manure has low phosphorus concentrations (Ndung’u et al., 2003; Okalebo et al., 2006; Vanlauwe et al., 2006). An opportunity therefore exists in managing the soil P through enhancing RP solubilization and P concentration in compost manure. Research work in the region has focused on the use of RP and compost as an alternative cheaper source of phosphorus. Different types of organic materials including crop residue, compost and animal manure have been shown to improve P solubility and thus availability to plants when added together (Ikerra et al., 1994; Savini et al., 2005). In addition, when certain types of natural RP are composted with organic manures, P solubilization is increased mainly through microbial solubilization (Kavitha and Subramanian, 2007; Khan et al., 2007) and solubilization by the organic acids released in the composting process (Singh and Amberger, 1998; Aria et al., 2010). Low phosphorus content of compost manure can thus be addressed through p-fortification with RP. Studies have also shown that the availability of phosphate to crops in acid soils is increased when composted (Ndung’u et al., 2003; Schefe et al., 2008). These studies mainly used Single Super Phosphate (SSP) and Triple Super Phosphate (TSP) sources of phosphorus. While these sources resulted in increase in the solubility and availability of P, their costs are prohibitive for resource poor farmers. The use of low cost sources of phosphorus in compost fortification would greatly improve their accessibility to farmers in the region. Different RP sources show differences in dissolution rates when used in enriching compost manure (Nyirongo et al., 1999; Sharif et al., 2011). The extent of RP solubilization by composting material vary with the reactivity of the RP, type of organic waste, compost to RP ratio and time of incubation ( Kumari and Phogat, 2008). In order to define application rates and codes of practice for compost use, it is essential to be able to predict the fertilizer effect of the compost and the availability of the nutrients contained relative to conventional inorganic fertilizers. It is therefore important to investigate affordable phosphorus management systems that involve recycling of less expensive natural resources such as organic materials which may be a more viable means of enhancing soil fertility in smallholder farms in the area. Little has, however, been done in the use of the less soluble Minjingu RP (MRP) in fortification of compost manure. The objective of this study is to therefore to determine the effectiveness of MRP fortified compost manure in enhancing phosphorus availability and improving maize yield in the acid soils of South Nandi District. MATERIALS AND METHOD Site description The research was conducted at three selected sites, Koibem, Kiptaruswo and Kapkerer, located in

South Nandi District of western Kenya (Table 1).

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Table 1. Location, altitude and agro-ecological classification of the experimental sites

Site Location Altitude (masl) Agro-ecological zone*

Koibem 000 09’ 28.2”N

340 54’ 31.9”E

1770 UM 1

Kiptaruswo 000 02’ 28.1”N

034 56’ 35.9”E

1582 UM 2-3

Kapkerer 000 00’ 31.9”N

34 48’ 14.6”E

1530 LH 1-3

* UM 1= upper midland; UM 2-3 = upper midland; LH 1-3 = lower midland; 1=humid, 2= sub-humid and 3= semi-humid

AEZ source: Jaetzold and Schmidt (2007)

The area receives a bimodal rainfall with the average annual rainfall range of 1800mm to 2146 mm. Long rains are experienced from March to August and short rains occur from September to January. Temperatures are fairly constant throughout the year with mean daily minimum and maximum of about 12oC and 29oC respectively, while mean annual temperature is 21oC. The predominant soils are dark red, well drained, deep, sandy to sandy loam texture and classified as nitisols (Jaetzold and Schmidt, 2007).

Table 2. Properties of the soils at the experimental sites

Site

Soil property Koibem Kiptaruswo Kapkerer

Texture

pH (water) 5.2 5.3 5.8

Olsen P(mg kg-1) 37 13 9

Total N (%) 0.3 0.2 0.1

Organic C (%) 3.7 2.7 1.2

Exch. K (g kg-1)

Exch. Ca (g kg-1) 2815 3472 3239

Exch. Mg (g kg-1) 82.2 83.7 81.7

Exch. Na (g kg-1)

Treatment combination and experimental design The experimental designed was Randomized Complete Block Design (RCBD) with three replications per site. This experiment was set up in September 2011 during the short rain (SR) and repeated in March 2012 during the long rain (LR) season. The repeat experiment was conducted on new plots in nearby adjacent farms to avoid phosphorus residual effects of the previous season’s application. The treatments were as follows: 1. Control (CM) - 0 kg P2O5 ha-1

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2. Rock Phosphate (MRP) - 60 kg P2O5 ha-1 3. Triple Super Phosphate (TSP) - 60 kg P2O5 ha-1 4. Compost Manure (CM) - 6 t ha-1 with 0 kg P2O5 ha-1 5. P-fortified Compost Manure (PCM) – 6 t ha-1 with 60 kg P2O5 ha-1 All plots received a uniform dose of 60 kg N ha-1 in the form of calcium ammonium nitrate applied in split application. Hybrid maize variety H513 and H614 were planted the in the SR and LR season, respectively, in plots measuring 3.6 m by 3.75 m at an inter-row spacing of 75 cm and an intra-row spacing of 30 cm. Weeding was done two weeks after germination and repeated in the 8th and 12th weeks. Stalk-borer was controlled by applying Actelic® 1% at a rate of 2 grams per plant. Compost preparation The two compost treatments were prepared by composting agro-organic wastes with or without P-fortification. The procedure used was as described in Ndung’u et al. (2003) with some modifications. Composting was done in pits measuring 5 m length x 1.5 m width x 0.3 m depth. The phosphorus fortification was done by adding pre-calculated rates of granulated Minjingu Rock Phosphate (MRP; 27-29% P2O5) to achieve a final phosphorus content of 60 kg P2O5ha-1. The different organic materials, ash and the MRP were each layered sequentially at predetermined amounts, and sprinkled with water as required to achieve moisture content of between 40-60% (Lekasi et al., 2003). The layering was repeated to achieve a heap height of about 1.5m. The compost heaps were turned after one month and thereafter every three weeks to facilitate even decomposition. During the subsequent turnings the compost was inspected to determine the stage of decay. When mature the compost was harvested, samples taken for composition analysis and stored in gunny bags in cool dry environment pending use. Data collection and Laboratory analysis Composite soil samples were taken on several spots at a depth of 0-30 cm in each of the experimental sites for soil characterization. The samples were air dried and ground to pass through 2 mm sieve. The samples were analyzed for soil pH (water), total nitrogen (Kjeldahl method), organic carbon (Walkley-Black wet oxidation method), exchange cations (K, Ca, Mg, and Na) and available phosphorus (Olsen extractant), all as described in Okalebo et al., 2002. The samples of the fortified and unfortified composts were analyzed for total nitrogen (Kjeldahl method), organic carbon (Walkley Black wet oxidation method),pH (water), and available phosphorus fractionated into water soluble and citrate soluble fractions following the procedures described in Okalebo et al., (2002). Phosphorus uptake in maize was measured on the ear leaf. Leaf samples were taken at the silking stage, dried and ground to pass through 1 mm sieve. Maize grain yield were determined at physiological maturity and expressed in kg ha-1 at 13% moisture content. The grain yield and uptake data were used to calculate two parameters that were used to compare the effectiveness of the p-fortified compost to the other P sources, namely the Agronomic Phosphorus Use Efficiency (PUE) and the Relative Agronomic Efficiency (RAE). The PUE measured the yield increase of the test phosphorus source per unit of added phosphorus whereas the RAE was computed as the ratios

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of the yield responses with test fertilizer to the respective yield responses of the reference fertilizer (TSP) at the same rate (i.e. 60 Kg P2O5 ha-1). The formulae used were as below: 1. Agronomic Phosphorus Use Efficiency (PUE)

2. Relative Agronomic Effectiveness (RAE)

Statistical analysis The data was subjected to analysis of variance and the treatment differences separated using the Least Significant Difference (LSD) test at P≤0.05 level of probability. Results and Discussion Phosphorus Use Efficiency (PUE) In Koibem and Kiptaruswo sites, during both the SR and LR seasons, the P-fortified compost had the highest PUE followed by TSP and RP respectively (Table 1 and Table 2). This means that P in the P-fortified compost was more available as it resulted in higher increase in grain yield per unit of added P. In general the LR season had higher PUE than the SR season for each corresponding treatment. In Kapkerer, the trends in PUE were different within and between seasons. In the SR season, TSP had a higher PUE than both P-fortified compost and RP. However, in the LR season, both TSP and P-fortified compost seemed to have similar PUE at 30 and 29.3 kg grain kg-1 P2O5 respectively. Both were nevertheless higher than the 15.2 kg grain kg-1 P2O5 obtained for the MRP. The P in the MRP was therefore least available when not composted.

Relative Agronomic Effectiveness (RAE)

During the SR season P-fortified compost had the highest RAE followed by compost then RP respectively (Table 1). In the LR season RAE was slightly higher probably because of the difference in maize variety and rainfall amounts. P-fortified Compost had the highest RAE of 103

followed by compost then RP with 68 and 42 respectively. In Kiptaruswo, during the SR season, P-fortified Compost had the highest RAE followed by RP and then compost respectively. The same trend was followed during the LR season. In Kapkerer, P-fortified Compost had the highest RAE

followed by RP then compost. During the LR season P-fortified Compost had the highest RAE followed by compost then RP. Mutuo et al. (1999) found comparable RAE values in Kenya. Effects of P source on maize yield Maize yield during LR season was higher than SR season probably, because of higher rainfall during the former. Irrespective of season, P fertilizers increased the yield of maize. Opala et al.

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(2012) noted similar P fertilizer influences on maize yield in western Kenya. Maize yield varied significantly with P source (Figure 2a and 2b). Triple super phosphate (TSP) and P-fortified Compost manure had the highest yield followed by Compost, MRP and lastly the Control. The response to P fertilizers implies that the soils are deficient in P. Kihara and Njoroge (2013) and Titonell et al. (2011) similarly noted that P is one of the important nutrients limiting production in soils of western Kenya.

The high yield under P fortified manure that is comparable to TSP could be attributed to enhanced availability of P due to composting. Rock Phosphate is generally known to have low solubility, hence the low maize yield. It is very likely that during composting, organic acids were produced, which solubilized RP therefore improving the availability of P (Singh and Reddy, 2011) compared to directly applied RP and compost. Several scientists have reported the importance of compost in increasing the solubilzation of RP (Chien 2003; Zayed and Motaal, 2005; Imran et.,al 2011). Similarly, Biswas and Narayanasamy (2006) documented the positive impact of RP-enriched organic fertilizer as effective organic fertilizer for enhancement of growth and yield of plants. The positive impact of composting is also reported by Nishanth and Biswas (2008) on wheat crop. MRP although relatively affordable did not perform better than the no treatment control; probably because of its poor solubility. This indicates that MRP at the rates applied, may not be of immediate benefit to the maize crop. The application of P-fortified Compost was superior to all the other treatments except TSP. Ndungu (2003) similarly observed increase in crop yield with fortification using TSP. Compost manure performed poorly probably because of the low P content. CONCLUSIONS Farmers in South Nandi use compost fertilizers to improve their farm productivity. However, the expense related to the compost preparation must be marched with yield increases that justify its use. This study shows significant benefits of using p-fortified compost than compost alone. The use of TSP, while resulting in significant yield increases, is likely to have lower economic returns than with P-fortified compost. Farmers should therefore be encouraged to use rock phosphate in their compost rather than compost alone. ACKNOWLEDGEMENT We are grateful to the McKnight Foundation which funded this study through the Collaborative Research Programme. We also thank the farmers of South Nandi District for allowing us use of their land for the study. REFERENCES Aria, M. M., Lakzian, A., Haghnia, G. H., Ali, R. B., Besharati, H. and Fotovat, A. (2010). Effect of Thiobacillus , sulfur , and vermicompost on the water-soluble phosphorus of hard rock phosphate. Bioresource Technology 101: 501-554. Benedek, S., Elfoughi, A. and Abdorhim, H. A. (2012). Effects of compost application on soil fertility of a Luvisol from Hungary. Archives of Agronomy and Soil Science 58: 103–106. Biswas, D. S. and Narayanasamy, G. (2006). Rock phosphate enriched compost: An approach to improve low-grade Indian rock phosphate. Bioresource Technology 97: 2243–2251.

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Chien, S.H., Adams F., Khasawneh, F. E. and Henao, J. (1987). Effects of combinations of triple superphosphate and a reactive phosphate rock on yield and phosphorus uptake by corn. Soil Science Society of America Journal 51: 1656-1658. Fageria, N. K., and Baligar, V. C. (2003). Fertility management of tropical acid soils for sustainable

crop production. In ‘‘Handbook of Soil Acidity’’ (Z. Rengel, Ed.), pp. 359–385. Marcel Dekker, New York.

Imran, M., Waqas, R., Nazli, Z., Shaharoona, B. and Arshad1, M. (2011). Effect of recycled and value-added organic waste on solubilization of rock phosphate in soil and its influence on maize growth. International Journal of Agriculture and Biology 13: 751–755. Jaetzold, R., Schmidt, H., Hornetz, B. and Shisanya, C. (2007). Farm Management Handbook of Kenya. Natural conditions and Farm Management Information. Part A. Western Kenya (Nyanza and Western Provinces). Kenya Ministry of Agriculture and German Government, Nairobi, Kenya. Kavitha, R. and Subramanian, P. (2007). Bioactive compost - A value Added Compost with Microbial Inoculants and Organic Additives. Journal of Applied Sciences 7: 2514-2518. Khan M. S., Zaidi, P. A. and Wani, A. (2007). Role of phosphate-solubilizing microorganisms in sustainable agriculture – A review. Agronomy and Sustainable Development 27: 29–43. Kihara, J. and Njoroge, S. (2013). Phosphorus agronomic efficiency in maize-based cropping systems: A focus on western Kenya. Field Crops Research 150: 1–8. Kimetu, J., Lehmann, J., Ngoze, S., Mugendi, D., Kinyangi, J., Riha, S., Verchot, L., Recha, J. and Pell, A. (2008). Reversibility of soil productivity decline with organic matter of differing quality along a degradation gradient. Ecosystems 11: 726–739. Kinyangi, J. (2008). Soil degradation, thresholds and dynamics of long-term cultivation: from landscape biogeochemistry to nanoscale biogeocomplexity. PhD dissertation, Cornell University, Ithaca, NY, USA, 161 pp. Kumari, K and Phogat, V. K. (2008). Rock phosphate: its availability and solubilization in the soil – a review. Agriculture Reviews 29: 108 – 116. Marenya, P. P. and Barrett, C. B. (2007). State-conditional fertilizer yield response on western Kenyan farms. Available online at: http://aem.cornell.edu/faculty_sites/cbb2/Papers/State_Conditional_Yield_Response_23Apr2007.pdf Mishra, M. M. and Bangar, K. C. (1986). Rock phosphate composting: transformation of phosphorus forms and mechanisms of solubilization. Biology Agriculture and Horticulture 3: 331-340 Mtengetia, E. E., Semoka, J. M. R. and Maliondoa, S. M. (2013). Assessment of maize response to Minjingu phosphate rock and triple superphosphate applied under different P-application strategies in a Ferralsol in Tanzania. Archives of Agronomy and Soil Science 59: 1323–1338. Nalivata, P. C. (2007). Evaluation of factors affecting the quality of compost made by smallholder

farmers in Malawi. PhD thesis, Cranfield University, UK. Nekesa, P., Maritim, H. K., Okalebo, J. R. and Woomer, P. L. (1999). Economic analysis of maize-bean production using a soil fertility replenishment product (PREP-PAC) in western Kenya. African Crop Science Journal 7: 423-437. Okalebo, J. R., Gathua, K. W. and Woomer, P. L. (2002). Laboratory Methods of Soil and Plant Analysis: A Working Manual. 2nd edition. TSBF-CIAT and Sacred Africa, Nairobi.

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Okalebo J. R., Woomer, P. L., Mukhwana, E. J., Musyoka, M. W., Ndungu, K. W., Kifuko, M. N. and Kiraithe, C. K. (2003). Evaluation of soil fertility management technologies (best bets) on yield and uptake of nitrogen and phosphorus by maize and legumes in western kenya: a six NGO study. African Crop Science Conference Proceedings 6: 480-488. Okalebo, J. R., Othieno,C.A Woomer,P.L.. Karanja,N.K Semoka,J.R.M. , Bekunda,M.A Mugendi, R. M. Muasya, A. Batino and. Mukhwana.E.J (2006). Available technologies for replenishing soil fertility in Africa. Nutrient Cycling in Agroecological Systems 76:153-170. Rajan, S., S .S. and Watkinson, J.H. (1992). Unacidulated and partially acidulated phosphate rock: agronomic effectiveness and the rates of dissolution of phosphate rock. Fertilizer Research 33: 267-277. Savini, I., Smithson, P. C., Karanja, N. K., and Yamasaki, H. (2005). Influence of Tithonia diversifolia and triple superphosphate on dissolution and effectiveness of phosphate rock in acidic soil. Journal of Plant Nutrition and Soil Science 169: 593-604. Schefe, C. R., Patti, A. F., Clune, T. S., and Jackson, W. R. (2008). Organic amendment addition enhances phosphate fertilizer uptake and wheat growth in an acid soil. Australian Journal of Soil Research 46: 686-693. Sharpley, A. and Moyer, B. (2001). Phosphorus forms in manure and compost and their release during simulated rainfall. Journal of Environmental Quality 29:1462-1469. Singh, C. P. and Amberger, A. (1998). Organic acids and phosphorus solubilization in straw composted with rock phosphate. Bioresource Technology 63: 13-16. Tittonell P., Vanlauwe, B., Corbeels, M. and Giller, K. E. (2008). Yield gaps, nutrient use

efficiencies and response to fertilizers by maize across heterogeneous smallholder farms of western Kenya. Plant Soil 313: 19–37.

Tra T., Duong, T., Penfold, C. and Marschner, P. (2012). Differential effects of composts on properties of soils with different textures. Biology and Fertility of Soils 48: 699–707.

Vanlauwe, B., P. Tittonell and J. Mukulama, (2006). Within-farm soil fertility gradients affect response of maize to fertilizer application in Western Kenya. Nutrient Cycling in Agroecosystems 76: 171-182.

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TABLES AND FIGURES

Table 2. Nutrient composition of the unfortified (CM) and p-fortified (PCM) compost

Nutrient CM PCM

pH (water) 8.2 8.2

Organic C (%) 5.4 5.4

Total N (%) 1.1 1.5

Olsen P (g kg-1) 431 446

Water Soluble P (mg kg-1)

Citrate Soluble P (mg kg-1)

Exch. K (g kg-1)

Exch. Ca (g kg-1) 4628 4926

Exch. Mg (g kg-1) 88.5 88.6

Exch. Na (g kg-1)

Table 3- Agronomic phosphorus use efficiency (PUE) Koibem

SR Season LR Season

Treatment Yield

(kg ha-1)

PUE (kg kg-1

P2O5)

Yield

(kg ha-1)

PUE (kg kg-1 P2O5)

Control 1700 - 2550 -

MRP 2100 6.7 3910 22.7

TSP 3300 26.7 4560 33.5

Compost 2400 - 4190 -

P-fortified compost 3400 28.3 4730 36.3

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Table 4. Agronomic Phosphorus Use Efficiency (PUE) at Kiptaruswo SR Season LR Season

Treatment Yield

(kg ha-1)

PUE

(kg kg-1 P2O5)

Yield

(kg ha-1)

PUE

(kg kg-1 P2O5)

Control 1700 - 1730 -

MRP 2400 11.7 2910 19.7

TSP 3100 23.3 3670 32.3

Compost 2300 - 2480 -

P-fortified compost 3400 28.3 3790 34.3

Table 5 Agronomic Phosphorus Use Efficiency (PUE) at Kapkerer SR Season LR Season

Treatment Yields

(kg ha-1)

PUE

(kg kg-1 P2O5)

Yields

(kg ha-1)

PUE

(kg kg-1 P2O5)

Control 1500 - 1460 -

MRP 2100 10 2370 15.2

TSP 3200 28.3 3220 29.3

Compost 1900 - 2510 -

P-fortified compost 3000 25.3 3260 30

Table 6. Relative Agronomic Effectiveness (RAE) of the different P sources at Koibem

SR Season LR Season

Treatment Yield

(kg ha-1)

RAE

(%)

Yield

(kg ha-1)

RAE

(%)

Control 1700 - 2550 -

MRP 2100 25 3910 68

TSP 3300 100 4560 100

Compost 2400 78 4190 82

P-fortified Compost 3400 117 4730 103

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Table 7. Relative Agronomic Effectiveness (RAE) of the different P sources at Kiptaruswo

SR Season LR Season

Treatment Yields

(kg ha-1)

RAE

(%)

Yield

(kg ha-1)

RAE

(%)

Control 1700 - 1730 -

MRP 2400 50 2910 61

TSP 3100 100 3670 100

Compost 2300 43 2480 39


Table 8. Relative Agronomic Effectiveness (RAE) of the different P sources at Kapkerer

SR Season LR Season

Treatment Yield

(kg ha-1)

RAE

(%)

Yield

(kg ha-1)

RAE

(%)

Control 1500 - 1460 -

MRP 2100 35 2370 52

TSP 3200 100 3220 100

Compost 1900 24 2510 60


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Figure 2a. Effect of P source on maize yield (kg/ha) in western Kenya during the SR Season

Figure 2b. Effect of P source on maize yield (kg ha-1) in western Kenya during the LR Season

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Evaluation of bean varieties (phaseolus vulgaris L) for resistance to Bean Common Mosaic Virus (BCMV) and Bean Common Mosaic Necrotic Virus (BCMNV) across a soil fertility gradient in Nandi South of Kenya *R. J.Uside,1 J. Ojiem2 , O. Kiplagat3, J. Lauren4, B. Medvecky4

*Corresponding author

Abstract Bean Common Mosaic and Bean Common Mosaic Necrosis are among the most devastating diseases of common beans (Phaseolus vulgaris L) in Kenya. These viral diseases cause more than 80% yield losses. Control by chemical method is difficult once they have set in. Use of resistant varieties offers a sustainable and economical solution. Observation survey was carried out to identify the experimental sites. .A field study was conducted for one season in the identified four sites across soil fertility gradient in Nandi south. Alpha lattice design was adapted for the experiment. The bean lines screened for BCMV and BCMNV included twenty three bean lines developed for resistance to bean root rot (BRR) and three phosphorus efficient bean lines selected from an earlier field screening of fifty Phosphorus efficiency lines. Two check lines, RWR 719 carrying resistance to BCMV and GLP-585 a commercial variety were included in the trial as control lines. Parameters scored were BCMV and BCMNV incidence, Aphid count, stand count and yield. Further screen house inoculation was done in the second season to confirm field results. The data was subjected to ANOVA using SAS 8.2 Statistical software and LSD at 5% level of significance was used to compare the means of the genotypes for all variables. The bean lines showed significant differences in resistance to both BCMV and BCMNV across soil fertility gradient. Six lines were resistant to BCMV while 15 were resistant to BCMNV. The line BCO-05/07 and BCO-05/18 were particularly resistant to both viruses. The P efficient lines were completely susceptible to BCMNV, but resistant to BCMV. These results indicate that both BRR and P efficient lines can be good sources of resistance to transfer BCMV and BCMNV resistance respectively to popular but susceptible bean varieties.

Key words: Phaseolus vulgaris L, Bean Common Mosaic, Bean Common Mosaic Necrotic Virus, Nandi South, Bean root rot and phosphorus efficiency INTRODUCTION Common Beans (Phaseoulus vulgaris L) is the most important pulse ranking second to maize as a food crop in Kenya (Republic of Kenya, 2012). It plays a significant role in human nutrition by providing more than 45% of total protein consumed. It contains high levels of lysine, which is low in cereal crops like maize making it a good complement in the diet (Allen and Edje, 1990). In Kenya, bean consumption per capita is estimated about 50 kg/year (FAO, 2007) but can be as high as 66 kg/yr in western Kenya (Buruchara, 2007). The properties of the carbohydrates found in common beans, along with their fiber content, make them ideal foods for the management of abnormalities associated with insulin resistance, diabetes and hyperlipidemia (Leterme and Munoz,

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2002; Raatz, 2013).). The crop also restores soil fertility through Biological Nitrogen Fixation (BNF) (Kannaiyan, 1999). Further, it has a high industrial potential for citric acid production. (Torodivic et al., 2008) Bean common mosaic virus (BCMV) and Bean common mosaic necrotic virus (BCMNV) are economically important diseases globally (Mavric et al., 2003). BCMV usually causes mosaic symptoms on susceptible bean cultivars while BCMNV cause systemic lethal necrosis on bean genotypes carrying dominant I gene (Silbernagel et al., 2001). Both viruses (BCMV) and (BCMNV) are seed borne and are transmitted by aphid species and mechanical inoculation up to 83% by seed (Movric and Susta-vozlic, 2004). The diseases (BCMV and BCMNV) cause up to 6-98% and 100% bean yield losses respectively (Mukeshimana et al, 2003). Both viruses can be found in the same area and infecting the same plant (Silbernagel et al., 2001)., combined infection cause severe damage. Bean genotypes with the I gene only are resistant to BCMV, but susceptible to the necrotic virus strain (BCMNV). But genotypes carrying the recessive gene (bc-u and bc-3) in the presence of the dominant I gene confers resistance to all known strains of BCMV and BCMNV. Cultivars with I,bc-3 and bc-u,bc-3 combinations are immune to all strains of BCMV and BCMNV while i, bc-3 genotypes are resistant to all strains of BCMNV but susceptible to some strains of BCMV ( Larsen et al., 2008; Larsen and Miklas, 2010). Previous efforts to control BCMV focused on routinely introgressing the I gene into the Andean and Mesoamerican gene pools (Kelly, 1997). Some of the varieties were introduced to Kenya as a control measure to bean root rot (BRR), one of the constraints limiting bean production in western Kenya. There was an anticipated necrotic reaction with the varieties that were introduced as a means of managing BRR. To mitigate the necrotic disease, new bean varieties were introduced to the region to provide a solution to the problem and this necessitated the work reported in this paper. The specific objective of the study was to determine the prevalence of BCMV and BCMNV across sites and evaluate the 26 new bean genotypes for resistance to the two diseases. .Materials and method Observational method survey to establish the occurrence of BCMV and BCMNV was conducted in Nandi south district across soil fertility gradient. The survey was conducted between November and October 2009 at podding stage. Twenty farms were randomly selected at each site from which beans were sampled for BCMV, BCMNV and aphid infestations. The procedure used to identify the farms was to select one farm after every four farms along the main and village access roads. Combinations of purposive and simple random sampling methods were used to select the bean fields and sampling sites. The main criteria for identifying BCMV in the field were the mosaic symptoms associated with stunting and Leaf malformation. BCMNV identification were in reference to symptoms associated with necrosis of apex leaves and vain necrosis, while aphid infestation was rated on a scale of 1-9, where, 1= no aphid, 3=one to five aphids, 5=five to ten aphids, 7=ten to fifteen aphids and 9=more than fifteen aphids found. The survey data was used to select bean evaluation experimental sites. Four positions were sampled per farm and 20 plants examined for disease incidence. Disease incidence was recorded as the number of plants infected and expressed as a percentage of the total number of plants observed. Data was analyzed using SAS 8.2 Statistical software and separation of means was by Least Significance Difference (LSD) test at ρ≤ 0.05.

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The bean genotype evaluation experiment was conducted in four sites (Koibem, Bonjoge, Kiptaruswo and Kapkerer) in Nandi South across soil fertility gradient. The experimental sites and specific farms that hosted the experiments were characterised by doing soil analysis Twenty six bean genotypes from two gene pools (twenty three bean genotypes bred for bean root rot resistance and advanced bean lines selected for Phosphorous efficient) were evaluated. Two varieties GLP-585 a commercial variety susceptible to BCMV disease and RWR719 bean variety with specific gene resistance to BCMV were used as controls. The 26 genotypes were subjected to field evaluation for viral disease reaction. The experiment was planted during the long rain of March 2010. The experiment was planted two weeks after the surrounding farmer’s farms had been planted with beans and also the virus susceptible variety GLP-585 was planted round the experimental fields three weeks earlier to insure sufficient natural virus innoculum in the sites. Prior to planting, the taste bean were treated with FansanD (20% w/w Thiram) at recommended rates (3g of chemical per 1kg seed).The aim of seed treatment was to protect the seed from bean root rot (BRR) fungi and bean stem maggot (BSM) that could set in due to late planting. Alpha lattice design was adopted for this experiment (Nguyen, 2002). Each variety was planted in a plot size of (1.5 x 2) meter square, with inter-row and intra-row spacing of 0.5 metres and 0.1metres respectively, one seed per hill. At each site, there were four genotypes in each block of 7meters square. There were a total of seven blocks replicated four times per site (total of 112 plots). No chemical spray was applied after emergence, to encourage insect vector population. Experimental fields were kept free of weeds throughout the experimental period. The parameters measured were, stand count seven days after emergence by counting the number of seedlings that had emerged and stand count at harvesting, Incidences of BCMV and BCMNV (determined 50-60 days after emergence corresponding to podding stage). The procedure of scoring was by marking of the first bean plant followed by scoring every second plant within the row to avoid biasness, a total of 20 plants were sampled in each plot. The virus symptoms were rated on a 1-9 CIAT scale (Van Schoonhoven and Pastor-Corrales, 1987; Mills and Silbernagel, 1992), where, 1= not, 3= slightly, 5= moderately, 7= severely and 9= completely diseased. Aphid colonies were assessed by counting the number of aphids present on a score scale of 1-9, where 1=no aphids), 3=1-5 aphids, 5=5-10 aphids, 7=10-15 aphids and 9= more than 15 aphids. Yield Data was obtained by sampling mature beans per plot and threshed separately. The grains were obtained, weighed using an electronic balance and plot grain yield was determined for each genotype. Data was analyzed using SAS 8.2 Statistical software and separation of means was by Least Significance Difference (LSD) test at ρ≤ 0.05. A correlation analysis was done to check the effect and significance of the bean viruses on other dependent and independent variables. Screen evaluation The bean genotypes that showed no symptoms for BCMV and BCMNV in the field were further tested under screen house. RWR 719 bean variety with resistance to BCMV was included as a control. GLP-585 was also included as local check which is susceptible to BCMV. The test Beans were planted in polythene pots of 20cm diameter by 25cm height. The planting was forest Soil, Gravel previously washed and farmyard manure in the ratio of 3:1:1. The experiment was laid as a Completely Randomized Design (CRD) with 3 replicates. Pots were filled, arranged in the screen house and watered. Bean varieties assigned random numbers were planted five seeds per pot, later thinned to three after emergence. Three treatments were applied; BCMV, BCMNV and None

Page 36

inoculated control plants. The pots were watered twice per day. The minimum and maximum screen house daily temperature was scored. Inoculum and Inoculation. The BCMV and BCMNV inoculum were obtained from diseased plants in the field experiment, collected separately and used to pre-infect Umbano a bean variety susceptible to the virus. The first and second trifoliate leaves of 15 days old inoculated umbano showing disease symptoms were harvested, insuring that plants infected with different virus were handled separately. The leaves were ground in a mortar and the paste was filtrated through two layers of blotting paper and plant sap extracted. The extracted sap was diluted ten times using 0.02 M KPO4 buffer pH (7.5) to obtain the inoculum (Mill and Silbernagel, 1992, Chiumia and Msuku, 2001). The diluted sap containing the virus was maintained at -40C. Seven days after emergence the inoculum was applied. The leaves of the beans were dusted with carborundum and gently rubbed with cotton swap previously dipped into the suspension of the virus inoculum. Two bean plants were inoculated and one served as a control. Dimethoate was applied on two weeks interval to prevent spread of virus from one plant to another by aphids. Reaction to bean virus was recorded from the 5th day after inoculation recommended by Chiumia and Msuku, 2001 and continued for the next 28 days, a 1 to 9 CIAT scale was used to determine the resistance, where,1 = no visible virus symptoms on both the inoculated and un-inoculated leaves, while 9 = severely diseased or dead plants. Statistical Analysis was by application of the PROC MIXED procedure in SAS (SAS institute 2001) version 8.2. Separation of means was done by least significant difference (LSD) at 5% probability. RESULTS Incidence of BCMV and BCMNV) in Nandi South The incidence of BCMV varied among the sites (Table 6). The disease incidence was highest in Kiptaruswo, whereas Bonjoge had the lowest incidence. Consequently, BCMNV was recorded with lowest percentage incidences a cross the sites (Table 1). BCMNV incidence was lowest in Kapkerer, whereas Koibem had the highest incidence of the disease. Table 1. Incidence of BCMV and BCMNV in Nandi South across soil fertility gradient Site BCMV

Incidence Percent Farms with BCMV

Site BCMNV incidence

Percent Farms with BCMNV

Kiptaruswo 61.50a 70 Koibem 8.2a 25 Koibem 55.30a 35 Kiptaruswo 3.8ab 25 Kapkerer 43.60ac 40 Bonjoge 2.5b 5 Bonjoge 35.25bc 70 Kapkerer 1.9b 5 Means in each column followed by the same letters are not significantly different at p = 0.05

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Resistance of bean genotypes to BCMV and BCMNV There were significant difference p ≤ 0.05 in resistance to BCMV among bean genotypes (Table 2). Seven genotypes showed resistance to BCMV and six were susceptible to BCMV. On the other hand eight genotypes were resistant to BCMNV and seven were susceptible to BCMNV. The bean genotypes that showed high susceptibility to BCMV incidentally showed low or no susceptibility to BCMNV and similarly for BCMV. However the resistant check RWR-719 showed resistance score 1.0 to BCMV while the susceptible local cultivar GLP-585 was susceptible to BCMV (score 4-6). The most common symptom displayed by the susceptible genotypes was leaf curling (plate 1). The BCMNV symptoms were expressed as shown in plates 2a and 2b. Plate 2a shows necrotic symptoms of BCMNV on KK-RR-B-05/25 and plate 2b is showing necrotic symptoms on RWR -719. Table: 2 Genotype reactions to BCMN and BCMNV virus stress in Nandi South-Long rain 20110

Genotypes BCMV BCMNV APHID KK-RRB05/21 5 1 2 KK-RRB05/31 5 1 3 GLP-585 (conrol) 5 1 2 KK-RRB05/34 5 2 2 KK-RRB05/35 4 2 2 KK-RR B-05 / 20 4 1 2 KK-RRB05/23 4 1 3 BCO-05/25 2 1 2 RWR 719 (Control) 1 8 3 BCO-05/35 1 5 2 BCO-05/07 1 1 2 KK-RCAL-27/A 1 6 2 MHR-34 1 6 3 XRAV-187 1 6 3 ME-2221-314 1 6 2 LSD 1.2 0.87 0.66

BCMV= bean common mosaic virus, BCMNV= bean common mosaic necrotic virus, APHID=Aphid Virus data scored on a scale of 1-9, where 1= resistant and 9 = susceptible. Aphids data scored on scale of 1=5, where 1= a few aphids present and 9 = many aphid present

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Plate 1 Bean common mosaic virus symptoms on KK-RR-B05/31 in Kapkerer Nandi South

Plate 2a: Advanced symptoms of BCMNV on susceptible bean variety (BCO-05/35) in Kapkerer- 2010

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Plate 2b severe necrosis symptoms on susceptible bean variety RWR-719 in Nandi south Correlation of disease (BCMV, BCMNV) with Aphid, dependent and independent variables Negative and significant correlation was observed between BCMV and FW1 (r = -0.304***), NSP (r = -0.15***) and YLD (r = -0.009*), while positive and significant correlation was observed between number of aphids and BCMV (r = 0.15**) (Table 11). However, negative and non significant correlation was observed between BCMV and STC. Negative and significant correlation was observed between BCMNV and STC (r = -0.330***), FW1 (0.120**), NPP (-0.144**), NSP (-0.011*), YLD (-0.09**) and BCMV (-0.34***) while positive and significant correlation was observed between BCMNV and APHID (r= 0.111** )

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Table: 11 Correlation of disease (BCMV, BCMNV) with Aphid, dependent and independent variables

STC Flw1 NPP NSP YLD APHID BCMV BCMNV STC 1.000

FLW1 -0.403*** 1.000

NPP -0.055 0.136** 1.000

NSP -0.057 0.0180 0.025 1.000

YLD

APHID

BCMV

BCMNV

0.440***

-0.240***

-0.003NS

-0.330***

0.0719ns

-0.415***

-0.304***

-0.120**

0.098

-0.076

-0.009

-0.144**

0.098***

0.004

-0.15***

-0.011*

1.000

-0.200***

-0.009*

-0.09**

1.000

0.15**

0.111**

1.000

-0.34***

1.000

STC=Stand count at harvest, 1STflower, NPP=number of pods per plant, NSP= number of seeds per plant, APHD=aphids and YLD=yield, BCMV=Bean common virus, BCMNV=Bean common mosaic necrotic virus, *, **, ***, ns →Significant at P =0.05, P=0.01 or P=0.001 and not significant respectively,

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Screen house evaluations The bean lines artificially inoculated with BCMV and BCMNV viruses in the screen house were infected with disease over time. The observed results showed significant difference (p˂ 0.05) among the genotypes. The BCMV symptoms were observed on; BCO-5/09, KKRCAL-288, BCO-5/43 and BCO-5/03 and GLP-585 (Figure 3). The highest infection (score 7) was on the check line GLP-2 (Figure 3). Infection occurred from the 10th day after inoculation (Figure 2). BCO-05/43 had shown resistance to BCMV under natural infection but expressed the viral symptoms under artificial infection (Figure 3) BCMNV symptoms occurred on genotypes KKRCAL-194 under screen house. The check RWR-719 showed higher infection of BCMNV (score-9) (Figure-3) under screen house evaluation. KKRCAL 194 had shown resistance to BCMNV in the field. There were no disease symptoms on the non inoculated plants. The virus treatment induced a range of symptoms in infected bean genotypes including; severe standing and leaf distortion (Plate 3 and 4). There were some restricted local lesions on the inoculated primary leaves of KK-R –CAL-288, KK-R-CAL-27A genotypes

Figure 2: BCMV and BCMNV disease progress in the screen house in all tested lines

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Figure 3: BCMV and BCMNV diseases scores in the screen house for the tested lines

Plate 3: Sever standing after BCMV inoculation

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Plate 4: Showing pinpoint necrosis and distorted leaves

DISCUSSION Resistance of bean genotypes to BCMV and BCMNV The significant differences in the resistance of the bean genotypes to BCMV and BCMNV viruses, shows that some of the bean genotypes carry the resistant genes to either of the viruses. High susceptibility to BCMV shows absence of the I gene that confers resistance to BCMV. The bean genotypes that showed BCMNV symptoms most likely carry the l gene that confers resistance to BCMV but reacts with the necrotic virus strain. The genotypes that showed resistance to both viruses may be carrying combined resistant gene for both viruses. Correlation of disease (BCMV, BCMNV) with Aphid, dependent and independent variables The negative and significant correlation between BCMV and flower and yield, shows that as BCMV virus increase, the flowers and the yield reduce. Kamelmanesh et al., 2012, reports that BCMV virus stress severely increases empty pods (88.4%) and decreases seed yield by 46.76 percent, The positive significant relationship between the aphid and both viruses, shows that increased number of aphids increases the virus diseases, this is expected because more aphid will increase the disease infection to a susceptible variety as long as the diseases inoculum is in the environment. Negative and significant relationship between BCMV and BCMNV, means one virus effect increases when the other reduces. This is true in the case where a genotype carrying I gene will have less of BCMV effect but more of BCMNV effect where the necrotic virus is available. The was negative and significant relationship between BCMNV, yield and yield component in the results. BCMNV causes a hypersensitive reaction known as black root on certain bean varieties that carry the dominant I gene, regardless of the temperature. This hypersensitive reaction can result in the death of whole plants and can cause yield losses of 100 percent (Mkeshimana et al.,2003 Screen house evaluations Some bean genotypes showed susceptibility to the viruses under screen house condition yet they were resistant under field conditions. This could be due to the genotype escaping Aphid infection in the field

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Leaf downward curling and distortion symptoms observed, confirm absence of resistance to BCMV in the infected genotypes. The presence of restricted local lesions on the inoculated primary leaves could be due to the presence of dual resistance (combination of dominant I gene with bc2 recessive gene) in the genotypes. Genotypes with dominant I gene alone, will progress from necrotic local lesions to spreading veinal necrosis on the primary leaf. This spreading necrosis soon goes systemic into the vascular tissue of the midribs, petioles and stems, followed by systemic veinal necrosis and vascular discoloration from top leaves to roots, then death usually within 10-14 days (silbernagel et al.,2001) CONCLUSION This study has identified 2 introduced bean root rot resistant genotypes (BCO-05/18 and BCO-05/07) that are resistant to both BCMV and BCMNV viruses.

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REFFERENCE Buruchara, R. (2007). Background information on Common Beans (Phaseolus vulgaris L.) in

Biotechnology,Breeding & Seed Systems for African Crops. http://www.africancrops.net/rockefeller/crops/beans/index.htm.

FAO. (2007). Food and Agriculture Organization of the United Nations. FAO Stat -statistical

database. FAO. http://faostat.fao.org/default.htm. FAO, 2010. FAOSTAT (Food and Agriculture Organization of the United Nations) (2010).

Statistics Division 2010. [Online] Available at http://faostat. Accessed 20/06/2010. Jaetzold, R., H. Schmidt, B. Hornets and C. Shisanya 2009. Natural condition and farm management

information Vol. 2, 2nd edition of farm management handbook of Kenya. Ministry of Agriculture, Kenya and the German Agency for Technical Cooperation (GTZ), Nairobi, Kenya.

Kamelmanesh M. M. , A. Namayandeh , H. R. Dorri , M. R. Bihamta, 2012 . Effects of Bean common

mosaic virus on Seed Yield, Yield Components and Phenological Phases of Common Bean (Phaseolus vulgaris L.) Under Field Conditions. 3. 2012; 28 (1) :39-52 URL http://spij.spii.ir/browse.php?a_code=A-10-1-526&slc_lang=en&sid=1

Kelly, J.D. 1997. A review of varietal response to bean common mosaic potyvirus in Phaseolus vulgaris. Plant Varieties and Seeds 10:1-6. Kornegay, J. 1992. BCMN: CIAT’s Point of view. Annual Report of the Bean Improvement Larsen, R.C and P.N. Miklas. 2010. Mapping resistance to Peanut mottle virus in common bean. Annu. Rep. Bean Improv. Coop. 53: Leterme, P. and C. Munoz, 2002. Factors influencing pulse consumption in Latin America. British

Journal ofNutrition88.Suppl.3,s251-s254. Mills, L.J. and M.J. Silbernagel. 1992. A rapid screening technique to combine resistance to haloblight and bean common mosaic virus in Phaseolus vulgaris L. Euphytica 58:201-208.8 Mavrič, I., Šuštar-Vozlič, J., Viršček-Marn, M., Meglič, V. 2003. Evaluation of disease resistance in common beans using molecular markers : abstracts of oral and poster presentations given at First joint conference of the International working groups on legume viruses (16th Meeting of IWGLV) and vegetable viruses (10th meeting of IWGVV), Bonn, Germany, August 4-9, 2002. Z. Pflanzenkr. Pflanzenschutz (1970) 110 (1): 95-96. http://aaas.bfuni.ijsi/junij2004/18movricpdf-13/6/2013 Movric l.,J. Vozlic, 2004. Virus diseases and resistance to Bean common mosaic and Bean common mosaic necrosis potyvirus in common bean(Phaseolus vulgaris L.).http://aaas.bfuni.ijsi/junij2004/18movricpdf-13/6/2013

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http://www.africancrops.net/rockefeller/crops/beans/index.htm

http://faostat.fao.org/default.htm

http://faostat/

http://spij.spii.ir/browse.php?a_code=A-10-1-526&slc_lang=en&sid=1

Mukeshimana G., L. Patrick Hart and J. D. Kelly, 2003 Extension Bulletin E-2894 • September 2003 (Major Rev. of E-1561) Odendo, M., David S., and Otsyula R.M., 2001. Impact of root rot resistant bean varieties in western

Kenya: Application of impact diagramming. Proceedings of PABRA Millenium Synthesis: A Workshop on Bean Research and Development in Africa over the Last Decade, Novotel Mount Meru, Arusha, Tanzania 28 May – 1 June 2001.

Otsyula R. M. and H. Echaire, 2008. Grain legumes. KARI Kakameg annual report 2008 KARI Kakamega pp 41-45 Otsyula R. M. R. U. Juma and M. Wambulwa, 2009. Grain legumes. KARI Kakameg annual report 2009 KARI Kakamega pp 30-37 Raatz, S., Nutritional value of field beans.2013. Rtrieved from- http://beaninstitute.com/health- benefits/nutritional-value-of-dry-beans/-2/7/2013 Republic of Kenya 2012. Economic Review of Agriculture. Central Planning Unit, Ministry of

agriculture, Government Printer, Nairobi.

Silbernagel, M.J., G.I. Mink, R.-L. Zhao & G.-Y. Zheng, 2001. Phenotypic recombination between bean common mosaic and bean common mosaic necrosis potyviruses in vivo. Arch Virol 146: Todorović, J., M. Vasić, V. Todorović, (2008). Pasulj I boranija. Institut za ratastvo i povrtarstvo, Novi Sad, Poljoprivredni fakultet, Banja Luka. Van Schoonhoven and Pastor-Corrales, M.A. (1987). Standard System for the Evaluation of bean

Germplasm. Centro Internacional de Agricultura tropical, cali, Colombia.

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http://beaninstitute.com/health-

T1a: The adaptation and acceptability of common bean varieties: the case for varietal diversity in smallholder farming systems (if paper is just for beans) T1b: The need for bean varietal diversity for adaptation and farmer acceptability in smallholder farming systems T2: The need (case?) for varietal diversity in smallholder farming systems (if we combine beans, soya, groundnuts and lablab in the same paper) Target journal: experimental agriculture Authors: Beth, Eunice (if we use her socioeconomic data), James, John, Julie, Kamwana, and Muthomi Intro

• Smallholder farmers in sub-Saharan Africa live in difficult, heterogeneous environments that are experiencing complex socioecological changes (migration of men & youth out of rural areas, strains on cultural soil decline, shifting climate patterns, emergence of novel pests and dieasees)

• Due to the centrality of agriculture in these areas, crop improvement efforts are critical for poverty reduction and food system improvement.

• This is particularly true for legumes due to their multiple roles: food security, income generation, nutrition, crop diversification(ojiem; Bationo, Fighting Poverty in Sub-Saharan Africa,: The multiple roles of legumes)

• Improved varieties can benefit the poorest households because they are simple technologies, local customs encourage sharing of seed, results can be seen in a short period

Materials and methods Methods

• Site characterization: (include 1 site map that integrates elevation, rainfall and temperature layers; problem is that the free software only allows us to create 1 layer at a time—can’t overlay).

• Germplasm: KK8, KK15, KK071 and KK072, 4 root rot tolerant bean varieties, were sourced from KARI Kakamega on an annual basis; in the last year (2013, two local bean varieties Alulu and Punda ((local landrace and variety from Tanzania, personal communication, Roselyn) were purchased from local farmers after finding that these were the varieties most widely grown

• Plot size: 4 m2; net plot 2.85 m2 • Stand establishment & loss across the season

o Stand counts taken at emergence (taken as 14 DAP), 21 and 28 days after planting and at harvest; Percent loss calculated as percent mortality of emerged plants

• Measurements (all agronomic characteristics and pests and disease incidence and severity evaluations were based on CIAT’s standard system for germplasm evaluation (van Schoonhoven & Pastor-Corrales, 1987)

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• The following evaluations were carried out at 50% flowering on 3 randomly selected plants/plot that were destructively sampled for:

o totalnumbers of nodules and numbers that are pink inside (fixing nodules) o bean root rot severity o aphid severity

• All sites were visited on a weekly basis and the diseases were scored on a random sample of 5 plants/plot at the appropriate growth stage (i.e. onset of flowering CBB and BCMV)

• Harvest: net plot plants dried; all components of yield assessed Data analysis

• Bean root rot, pods/plant, seeds/pod and common bacterial blight had normal distributions and thus were ok for doing an ANOVA

• Grain yield, % mortality (14-28 days, 28-harvest) were ok for ANOVA after a log transformation

• Aphid scores and the foliar diseases BCMV, Leaf Rust and Anthracnose have too little variation to be analyzed by standard means; we use classification trees to explore the incidence of the disease by site and variety (% plots showing incidence of the disease in a particular)

Results Rainfall(we have LR2013 and the SR2013 is in progress)

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Main discussion points Additional points for discussion

• Looking at the overall productivity of beans and the other legumes across seasons, we can see that we still don’t have the right suite of germplasm for our higher elevation sites. Most of Kenyan highland populations are in the mid-altitude zoneOur overall collection of le

Conclusions

• No single variety has all the attributes smallholderfarmers value • No single variety has the capacity to withstand the biotic and abiotic stresses occurring in

their environment • Farmer landraces that have the ability to persist in these environments should be scrutinized

to understand the factors that contribute to their survival •

KK 15

• bush bean with medium black seeds (specify 100 seed weight) • introduced from Rwanda as part of a nursery of root rot tolerant varieties (Highlights CIAT

in Africa, No 18, December 2004) • came from KK15,has significantly more nodules compared to the other 3 varieties across

four (Table). This is likely related to Black bean types are known to produce many adventitious roots (Román-Avilés, Snapp, & Kelly, 2004)which is associated with root rot tolerance and iwould be expected to have more living root tissue for nodules to attach to. In all seasons more than 80% of the nodules were pink inside, indicating they were actively fixing.

Site Fixing Nodules

variety LR2011 SR2011 LR2012 SR2012 LR2013 Kapkerer

KK071 17 45.9 54.2 68 61 KK72 30 53.2 54.8 63 63 KK15 50 83.3 88.9 67 85 KK8 np 45.3 54.8 77 75 Alulu np np np np 69 Punda np np np np 88

Kiptaruswo

KK071 27 65.7 75.7 63 77 KK072 21 75.7 82.1 67 76 KK15 29 109.2 107.8 90 100 KK8 np 97.6 79.8 71 69 Alulu np np np np 67 Punda np np np np 80

Koibem

KK071 25 64.3 64.4 66 61

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KK072 25 76.3 87.0 69 68 KK15 24 97.6 109 85 78 KK8 np 79.5 86.4 74 69 Alulu np np np np 73 Punda np np np np 69

P(Var) NS 0.0000 0.000 0.01

LSD.05 NS 9.92 10.18 8.8 CV 72.82 25.57 27.51 26.35

ns=not significant; np= not planted 2. Pests and diseases observed on plants destructive sampling at 42 days after planting Root rot, bean stem maggot and aphid infestation Except for bean fly in SR 2011 and aphids in LR 2011 and LR 2012, highly significant, consistent differences (p< 0.01) were observed across the 3 seasons (Table ).

Site

Root rot severity (BRR)

Bean fly (Larvae + pupae)

Aphid severity

Variety LR2011 SR2011 LR2012 LR2011 SR2011 LR2012 LR2011 SR2011 LR2012 Kapkerer

KK071 1.9 4.2 3.9 5.0 3.0 2.1 1.1 2.0 1 KK72 3.2 3.9 4.1 1.2 2.3 1.0 1.1 2.1 1 KK15 1.9 3.4 3.4 5.0 2.7 2.3 1.1 2.8 1 KK8 * 3.4 3.3 * 2.9 1.4 * 2.1 1

Kiptaruswo KK071 1.8 4.8 4.1 4.1 5.4 2.4 1.7 4.4 1 KK072 2.8 4.8 4.3 1.7 5.0 2.1 1.7 4.1 1 KK15 1.9 4.0 2.8 4.9 4.0 2.4 2.2 4.2 1 KK8 * 4.9 3.0 * 4.9 2.2 * 3.8 1

Koibem KK071 1.0 4.7 3.1 3.4 4.6 2.3 1.3 4.9 1 KK072 3.0 4.2 3.7 1.0 4.1 0.7 1.3 4.6 1 KK15 1.8 4.0 2.6 4.4 4.2 2.4 1.3 5.0 1 KK8 * 4.4 2.9 * 4.4 1.7 * 4.4 1

P(Var) 0.0000 0.004 0.0000 0.0000 ns 0.0070 ns 0.01 ns

LSD.05 0.30 0.39 0.42 0.94 NA 0.70 NA 0.34 NA CV 26.25 17.16 22.43 50.71 40.69 65.37 26.77 17.02 22.27

Across all 3 seasons, KK15 had significantly less root rot than KK72 andKK71 and KK8 showed intermediate root rot susceptibility compared to the two other varieties. There were highly significant differences in the numbers of bean stem maggots and pupae found on plant stems in two of the three seasons. KK072 proved to be a less attractive host to the bean fly than the other 3 varieties (Table), which were not significantly different from one another.

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The aphid data was inconclusive. Based on information from another experiment, this may be because aphid infestation is more serious later in the growing season compared to when the plants were sampled. Severity of foliar diseases Several foliar diseases were observed on the beans during the 3 growing seasons. (Table). Among these diseases, bean common mosaic virus (BCMV) and common bacterial blight (CBB) were observed in all 3 seasons and were generally characterized by highly significant site x variety interactions.

Site

BEAN COMMON MOSAIC

COMMON BACTERIAL BLIGHT

ANTHRACNOSE LEAF RUST

variety LR2011 SR 2011

LR 2012

LR 2011

SR 2011

LR 2012

LR 2011

SR 2011

LR 2012

LR 2011

SR 2011

LR 2012

Kapkerer KK071 4.0 2.2 2.0 1.9 1.0 1.3 - - 2.0 2.6 1.0

KK 072 3.9 1.3 2.1 2.0 1.0 1.0 - - 1.9 1.9 1.0 KK 15 3.3 1.0 1.0 3.0 1.0 3.1 - - 1.0 3.1 1.8

KK8 * 1.9 1.3 * 1.0 1.0 - - 1.3 2.4 1.2 Kiptaruswo

KK071 5.0 2.0 1.0 1.0 1.7 1.0 - - 2.9 2.8 1.0 KK072 4.0 2.6 1.0 1.0 1.7 1.0 - - 3.2 2.7 1.0 KK15 3.4 1.6 1.0 1.0 3.1 2.2 - - 1.2 4.2 1.9

KK8 * 2.3 1.0 * 1.7 1.2 - - 3.1 3.4 1.0 Koibem

KK071 1.0 1.0 1.6 3.9 1.3 1.2 - - 3.3 3.0 1.0 KK072 1.0 1.0 1.6 3.9 1.3 1.2 - - 3.1 2.8 1.2 KK15 1.0 1.0 1.0 1.2 1.7 2.1 - - 1.0 3.8 1.3

KK8 * 1.0 1.6 * 1.4 1.1 - - 2.6 3.0 1.0 P(Var) Except where noted

S x V 0.01

S x V 0.02

0.02 S x V 0.0000

S x V 0.01

S x V 0.009

_ - 0.0000 0.0000 0.0000

LSD.05 S x V 0.62

S x V 0.64

0.38 SxV 0.62

S x V0.65

S x V 0.50

_ - 0.41 0.22

CV 22.27 43.71 52.15 31.24 46.35 34.46 - - 46.16 25.46 33.57 BCMVwas unimportant at Koibem compared to the other 2 sites in the first two seasons. In LR2012, there was no disease at Kiptaruswo. Across seasons, where ever the disease was present, KK15 showed significantly superior tolerance compared to the other varieties. CBB was present at Koibem in all three seasons but this was not true for the other sites, where it was not observed in at least one season. KK15 did not behave consistently across sites in LR 2011.

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At Koibem, CBB was significantly less severe on KK15 compared to the other varieties but at Kapkerer it was significantly more severe. In the SR2011, CBB was not observed at Kapkerer and was also not not true at Kapkere where was significantly more severe but had a significantly high as it was the most susceptible was the most

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Characterization of the project sites using GIS techniques As already explained earlier, the smallholder systems are characterized by a high level of biophysical and socio-economic variability. It is important to understand the patterns of this variability to guide the testing of options, generation of recommendation domains and scaling out of technologies. It is in this regard that the project felt it necessary to conduct additional characterization of the project sites in order to determine the dominant sources of the biophysical and socio-economic variation that need to be factored into the design and implementation of research in the target smallholder systems. GIS techniques were used to facilitate this characterization, which focused on rainfall, temperature, altitude, soil organic carbon levels (proxy for soil productivity fertility), and pest and diseases (root rot, halo blight, bean fly, aphids, etc) Some of the preliminary maps produced are shown below.

Challenges: The project considers GIS supported characterization to be an important step to hypothesis formulation, targeting of options to be tested, and guiding scaling out activities. However, a number of challenges exist:

• The maps are not as accurate as should be due to low resolution of data. The project intends to increase data points to improve the accuracy of the information contained in the maps.

• The project is lacking expert to support for GIS work.

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Appendix B: Publications and training summary The following are the draft papers being prepared for submission to journals for publication:

i. Influence of lablab residues on incidence and severity of root rot and yield of bean intercropped with maize (Mugambi1, I. K., Muthomi1, J. W., Ojiem2, J., Chemining’wa1, G. N. and Nderitu3, J. H.)

ii. Effects of p-fortified compost manure on p-uptake and maize yield in smallholder mixed farming system of western Kenya (M. A. Okumu1, S. M. Mwonga 1, I M. Tabu1, J. Ojiem2 and J. Lauren3) Target Jounal: Experimental Agriculture

iii. Evaluation of bean varieties (phaseolus vulgaris L) for resistance to Bean Common Mosaic Virus (BCMV) and Bean Common Mosaic Necrotic Virus (BCMNV) across a soil fertility gradient in Nandi South of Kenya (R. J.Uside, J. Ojiem , O. Kiplagat, J. Lauren, and B. Medvecky) Target Journal: African Crop Science Journal

iv. The adaptation and acceptability of common bean varieties: the case for varietal diversity in smallholder farming systems (if paper is just for beans) (Beth, Eunice (if we use her socioeconomic data), James, John, Julie, Kamwana, Muthomi))Target journal: Experimental Agriculture

The following is an update on Capacity Building activities: Three students were supported by the project to conduct research for their MSc theses in 2013:

i. Ms Monica Okumu Egerton - University, Njoro, Kenya. These title: Effect of P-fortified compost manure on maize yield in smallholder mixed farming systems in Nandi South, Western Kenya.

Progress: Monica completed the field work in the 2013 long rain season. She is currently analyzing the maize tissue for P uptake in our soil science labs, which she is expected to finish in the next two weeks and incorporate the results into her draft paper (see Appendix A above). In the mean time Monica is writing her thesis and is expected to submit it for examination by the end of the year and if possible graduate in May 2014.

ii. Ms Ida Mugambi- University of Nairobi, Kenya.

Theses title: Reaction of grain legumes to diseases under varying eco-climatic zones in Nandi South district. Ida Mugambi.

Progress: Data analysis and thesis write up completed in May 2013, Thesis submitted for examination early June 2013, defended thesis early August 2013. Graduated with MSc Agricultural Resource Management on 23/8/2013

ii. Ms Anne Kadaari Kivisi-University of Nairobi, Kenya. Theses title:Management of root rot and bean fly in legumes by use of seed dressing. Progress: Still developing her thesis research proposal for MSc Agricultural Resource Management. Expected to carry out field research and green house experiment.

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Appendix D: M&E Framework

evaluation questions INDICATORS Methods Status Remarks and follow on plan

Adoption of legumes to improve system diveristy

Are farmers successfully growing legumes in the Nandi systems?

Improved understanding of the Nandi farming system Key farmers knowledge and skills in legume management Diversity of legumes in the system and farming methods Key farmers’ varietal preferences and reasons (food security, nutrition and income) Proportion of farmers increasing acreage of selected legumes/varieties Crop management options proportion of famers applying them Key farmers knowledge and skills in legume management and proportion of famers applying them Proportion of farmers reporting increased yield % farmers testing

In year 1 a participatory analysis of the Nandi farming system will be undertaken with farmers and researchers to provide data on the key aspects of the system, need for legume integration and selection of farmer preferred verities that are relevant to their agro ecologies This will provide a basis for comparison of changes in the farming system at the end of project implementation. In year one on Varietal screening & socioeconomic assessment of Multipurpose legumes will be undertaken in year one to expose farmers to provide a basis for farmers choice of alternative legumes with potential for improving the productivity of their farming systems; to determine the adaptability of the legume species and varieties in the different agro ecological zones of Nandi County; and to facilitate participatory evaluation and selection of preferred legume choices by farmers The information will provide a basis for farmer decision making for choice of legumes to grow in the system. This will provide important literature to inform the end of project evaluation. During the project implementation data will be collected on selected sites/farmers to detail their preferred legume choices and methods of production. Randomly selected farmers will be followed for their experiences of adopting given legumes, reasons and success and well as changes associated with their action. This

Project is on track. Systems diagramming was undertaken involving a total of 57 farmers drawn from the project implementation sites (Kapkarer Koibem, Kiptaruswo) comprising 23women and 34 men. Reports are available on farmer legume preferences, and adoption in the subsystem. It was reported that gave farmers knowledge on grain legumes that are effective in suppressing Striga weed, importance of maintaining weed free seed production fields and soybean & lablab are good in regenerating poor soils especially at Kiptaruswo. The knowledge helped farmers determine which legume options to take on-an indicator towards changes in legume diversity in the system. The following legumes were preferred:

The project is on tract on the various aspects, reporting the indicators. Legumes introduced include Lablab; groundnut, field pea, pigeon pea and cowpea and soybean. Annual reports show; beans. There performance has varied based on a number of factors including weather, pests and diseases. A detailed picture across the all the legumes will be obtained in year four after the household survey. Plan: during the mid-year review meeting-the end of project evaluation will be discussed, and integration of specific aspects for indictors on this aspect discussed.

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evaluation questions INDICATORS Methods Status Remarks and follow on

plan legume based technologies for farming system improvement Number of production constraints identified and addressed by researchers in each farming system Number of technologies introduced for improving farming systems

will be reported on every year. In the final year, farmers who are participating in the project will engage in systems diagraming to provide data on the indicators for this questions.

Farmers during a training workshop on legume utilization and value addition reacted favorably to newly introduced legume dishes with soybean products being the most popular 62 farmers from 4 farmer groups in Nandi and farmers from 3 groups in Vihiga counties go skills in proper seed production techniques

How has production of legumes improved farmer livelihoods of smallholder farmers in western Kenya?

Farmer understanding of the role of legumes in system improvement Farmer utilization of legumes introduced in the system Productivity of the farming systems improved % change in legume productivity Change in household income

During project implementation analysis will be made on production data (of participating famers) every season to document performance of the various legumes in the system. An end of project household survey will be conducted to assess changes in incomes and associated livelihoods across the participating households in the project sites.

In year 3it was reported legumes have improved farmers livelihoods through consumption and surplus for sale as a result of the land being more productive and different products were made from different legumes. Lablab, groundnut and field pea recipes were more preferred to pigeon pea and cowpea recipes. Soya meat was most preferred in three out of four sites, followed by mandazi. Soya meat was preferred by both genders across all sites except for Kapkerer where it was rated low. Generally soya bean was rated highly for its diverse usage.

Project undertakes analysis of production data (details to be got from the project)

Plan: During the mid-year review meeting, discussions will be held on the plans for the end of project household survey. Any support to the project will depend on the outcomes of this meeting.

ISFM How are improvements in soil health benefiting Nandi farmers?

Proportion of farmers increasing adoption of ISFM options

Soil analysis will be undertaken by the project every end of season. Reports from soil analysis will be reviewed to analyze change in soil N levels

Soil N are done every season and data provided in annual reports

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evaluation questions INDICATORS Methods Status Remarks and follow on

plan What are the significant changes on soil fertility and productivity as a result of integrating multiple legumes in the Nandi farming system?

Increased acreage under ISFM practices Increased levels of soil nutrients Yields levels associated with improved soil fertility % change in soil N levels

The analysis from yield levels will be compared with change in soil N levels to establish any associations between the two.

In year 3 it was reported that trends in nodulation and nitrogen fixation were quite similar to those observed in the previous seasons. Only sites had significant effect on both nodulation and the number of nodules fixing nitrogen. The average number of nodules per plant ranged from 17–24 and similar to the previous seasons. Kapkerer had significantly (p<0.01) higher average number of nodules per plant (22.7) than Koibem (17.7). Sites had a significant effect on grain yield in LR 2012. Grain yield performance was best in Kapkerer with the highest mean yield of 1.39t/ha, while Kiptaruswo had the lowest mean grain of 0.77 t/ha.

Major project evaluation questions and indicators of success Question 1: Are famers successfully growing legumes in Nandi systems? Yes, indicators:

• 500 farmers are growing assorted legumes in Nandi South since the inception of the project • The number new legumes being grown (in addition to bean) include groundnut, soybean and lablab • Varieties preferred are soybean (SB19 and SB25), groundnut variety CG7 and lablab variety Rongai • The varieties are preferred for: food security (SB19 and lablab Rongai), income (groundnut CG7) • More than 200 farmers have participated in research activities of the project since inception, about 120 of these have scaled up from 0.5

to 2.0 acres. All the 120 farmers who have scaled up have realized increased grain legume production

Question: How has production improved farmer livelihoods in western Kenya? • Up to 80% of the research farmers who have scaled up legume production are now selling grain the market (groundnut, soybean and

lablab). Question: What are the significant changes in soil fertility and productivity as a result of integrating multiple legumes in Nandi systems?

• Increased acreage of land under soil improving legume species and varieties • Improved productivity of the legumes and the cereals grown following legumes.

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Appendix F: DDS

DOCUMENTS AND DATA STORAGE (DDS) SYSTEM Project data is processed and stored at a central place on a project computer dedicated to data storage. A back-up copy is stored on an external hard disk. This process is managed by the project administrator. The data stored includes reports, raw data, analyzed data, financial reports and photos. The structure of the DDS is given the diagram below.

Data sharing plan: there are no formal data sharing arrangements in place as of now. Most of the sharing has been between project partners. No external request has been received so far. The movement of data in and out of the DDS has been managed via the drop box.

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Appendix G: photos (project implementation) Implementation of verification trials

Farm with Striga in Kapkerer site. Legumes were introduced to suppress striga.

Multipurpose legumes planted in Striga infested field.

Maize performing well in a after Striga suppressed by legumes.

Varietal screening trial

Legume screening trial plots in Koibem site

Effect of root rot on local bean variety (Alulu) in the varietal screening trial.

Nodules on bean roots in the varietal screening trial

Lime trial activities

Lime application in the trial plots

Lime-applied soybean plot in the lime trial at Kiptaruswo

Bean nodules sampled from the lime trial plots.

Implementation of storage pests control strategies

A farmer preparing to apply solar sterilization in the control of storage pests

A farmer mixing wood ash with grain to control storage pests.

A farmer shaking a mixture of maize grain and actelic

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Bean aphids trial

Sticky yellow cards used to trap winged aphids.

Field Assistant collecting data the bean aphids trial.

A youth being trained on identification of winged aphids on a yellow sticky card.

Implementation of community seed bulking activity

Joan Inzira, a farmer in Kapkerer posing in her groundnut seed bulking plot.

Leah Sigei, a farmer in Koibem standing in her bean (KK8) seed bulking farm.

Kapkebon farmer group in Kapkerer weeding their bean KK8 bulking plot.

Nandi and Vihiga farmers participation in Kari Kibos open day

Project stand at KARI Kibos open day.

Project farmers demonstrating how to prepare soya milk at KARI Kibos open day.

Project farmers interacting with other visitors during the KARI Kibos open day

Paper writing workshop in progress at Maseno Agricultural Training Centre

Formulating strategy for the workshop

Group work in progress

Another group discussing strategy

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Project mid-year review workshop at KARI Kibos

The Project PI presenting the workshop objectives and expected outputs.

A section of participants at the mid-year review workshop.

An NGO partner reporting on progress made

The Tudor Trust visit to the project activities in Nandi South (November 2012)

Observing soybean bulking plot in Vihiga.

Observing varietal screening trial plots in Kapsengere site.

Looking at solar sterilization in progress.

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The McKnight Foundation External Wire Transfer Request Form

Note: all requested information is required. You may not know all the information. For that reason, we recommend you contact your bank when completing this form.

Grantee information:

Legal name of grantee organization: KENYA AGRICULTURAL RESEARCH INSTITUTE

Grant number: 10-473

Name of individual completing form: JOHN O. OJIEM

Email address of individual completing form: [email protected]

Transfer funds to (USA correspondent bank):

U.S.A. Correspondent Bank Fed ABA Number and CHIPS ABA Number: BARCU33

U.S.A. Correspondent Bank Name & City: BARCLAYS BANK PLC, 75 WALL STREET, NEW YORK, NY

For credit to (local bank):

Bank/Country Code number and/or Branch/Swift Code number and /or Local Bank Account Number: BARCKENX009

Local Bank’s Complete Name: BARCLAYS BANK OF KENYA LIMITED

Local Bank Street Address: OGINGA ODINGA STREET

Local Bank City, Region/District, & Country: KISUMU, KENYA

For further credit to:

Beneficiary's Account Number: 2027299655

Beneficiary's Account Name: KARI KIBOS MULTIPURPOSE LEGUMES PROJECT Name of Beneficiary KARI KIBOS

Provide contact information for your local bank:

Name of individual to contact at bank: BRIAN OGILA

Telephone number and/or email address: 254-723051869/ email:[email protected]

DEFINITIONS: LOCAL BANK ADDRESS: If the full address is not available, then the Bank Code and the city where the bank is located must be given.

BANK/ COUNTRY CODE NUMBER: Countries have a different name for these codes. For example, in the USA they are ABA codes; in England-Sort codes;

in Germany-BLZ codes. They are usually numeric and are very important to determine which branch of a particular bank they belong to.

SWIFT CODE: This helps computer direct funds to the correct bank and branch.

annual progress report i. overview -...

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